:warning: You can use these for preparing for an interview but most of the questions and exercises don't represent an actual interview. Please read [FAQ page](faq.md) for more details
:stop_sign: If you are interested in pursuing a career as DevOps engineer, learning some of the concepts mentioned here would be useful, but you should know it's not about learning all the topics and technologies mentioned in this repository
Ethernet simply refers to the most common type of Local Area Network (LAN) used today. A LANāin contrast to a WAN (Wide Area Network), which spans a larger geographical areaāis a connected network of computers in a small area, like your office, college campus, or even home.
Packets that are sent on the ethernet are always coming from a MAC address and sent to a MAC address. If a network adapter is receiving a packet, it is comparing the packetās destination MAC address to the adapterās own MAC address.
When a device sends a packet to the broadcast MAC address (FF:FF:FF:FF:FF:FFā), it is delivered to all stations on the local network. Ethernet broadcasts are used to resolve IP addresses to MAC addresses (by ARP) at the data link layer.
An Internet Protocol address (IP address) is a numerical label assigned to each device connected to a computer network that uses the Internet Protocol for communication.An IP address serves two main functions: host or network interface identification and location addressing.
A Subnet mask is a 32-bit number that masks an IP address and divides the IP addresses into network addresses and host addresses. Subnet Mask is made by setting network bits to all "1"s and setting host bits to all "0"s. Within a given network, out of the total usable host addresses, two are always reserved for specific purposes and cannot be allocated to any host. These are the first address, which is reserved as a network address (a.k.a network ID), and the last address used for network broadcast.
Private IP addresses are assigned to the hosts in the same network to communicate with one another. As the name "private" suggests, the devices having the private IP addresses assigned can't be reached by the devices from any external network. For example, if I am living in a hostel and I want my hostel mates to join the game server I have hosted, I will ask them to join via my server's private IP address, since the network is local to the hostel.
A public IP address is a public-facing IP address. In the event that you were hosting a game server that you want your friends to join, you will give your friends your public IP address to allow their computers to identify and locate your network and server in order for the connection to take place. One time that you would not need to use a public-facing IP address is in the event that you were playing with friends who were connected to the same network as you, in that case, you would use a private IP address. In order for someone to be able to connect to your server that is located internally, you will have to set up a port forward to tell your router to allow traffic from the public domain into your network and vice versa.
A router, switch, and hub are all network devices used to connect devices in a local area network (LAN). However, each device operates differently and has its specific use cases. Here is a brief description of each device and the differences between them:
1. Router: a network device that connects multiple network segments together. It operates at theĀ network layer (Layer 3)Ā of the OSI model and uses routing protocols to direct data between networks. Routers use IP addresses to identify devices and route data packets to the correct destination.
2. Switch: a network device that connects multiple devices on a LAN. It operates at theĀ data link layer (Layer 2)Ā of the OSI model and uses MAC addresses to identify devices and direct data packets to the correct destination. Switches allow devices on the same network to communicate with each other more efficiently and can prevent data collisions that can occur when multiple devices send data simultaneously.
3. Hub: a network device that connects multiple devices through a single cable and is used to connect multiple devices without segmenting a network. However, unlike a switch, it operates at theĀ physical layer (Layer 1)Ā of the OSI model and simply broadcasts data packets to all devices connected to it, regardless of whether the device is the intended recipient or not. This means that data collisions can occur, and the network's efficiency can suffer as a result. Hubs are generally not used in modern network setups, as switches are more efficient and provide better network performance.
A collision domain is a network segment in which devices can potentially interfere with each other by attempting to transmit data at the same time. When two devices transmit data at the same time, it can cause a collision, resulting in lost or corrupted data. In a collision domain, all devices share the same bandwidth, and any device can potentially interfere with the transmission of data by other devices.
A broadcast domain is a network segment in which all devices can communicate with each other by sending broadcast messages. A broadcast message is a message that is sent to all devices in a network rather than a specific device. In a broadcast domain, all devices can receive and process broadcast messages, regardless of whether the message was intended for them or not.
A router is a physical or virtual appliance that passes information between two or more packet-switched computer networks. A router inspects a given data packet's destination Internet Protocol address (IP address), calculates the best way for it to reach its destination, and then forwards it accordingly.
Network Address Translation (NAT) is a process in which one or more local IP addresses are translated into one or more Global IP address and vice versa in order to provide Internet access to the local hosts.
If youāre using a proxy server, internet traffic flows through the proxy server on its way to the address you requested. The request then comes back through that same proxy server (there are exceptions to this rule), and then the proxy server forwards the data received from the website to you.
- A client node sends an SYN data packet over an IP network to a server on the same or an external network. The objective of this packet is to ask/infer if the server is open for new connections.
- The target server must have open ports that can accept and initiate new connections. When the server receives the SYN packet from the client node, it responds and returns a confirmation receipt ā the ACK packet or SYN/ACK packet.
- The client node receives the SYN/ACK from the server and responds with an ACK packet.
From [wikipedia](https://en.wikipedia.org/wiki/Round-trip_delay): "the length of time it takes for a signal to be sent plus the length of time it takes for an acknowledgment of that signal to be received"
SSL handshake is a process that establishes a secure connection between a client and a server.
1. The client sends a Client Hello message to the server, which includes the client's version of the SSL/TLS protocol, a list of the cryptographic algorithms supported by the client, and a random value.
2. The server responds with a Server Hello message, which includes the server's version of the SSL/TLS protocol, a random value, and a session ID.
3. The server sends a Certificate message, which contains the server's certificate.
4. The server sends a Server Hello Done message, which indicates that the server is done sending messages for the Server Hello phase.
5. The client sends a Client Key Exchange message, which contains the client's public key.
6. The client sends a Change Cipher Spec message, which notifies the server that the client is about to send a message encrypted with the new cipher spec.
7. The client sends an Encrypted Handshake Message, which contains the pre-master secret encrypted with the server's public key.
8. The server sends a Change Cipher Spec message, which notifies the client that the server is about to send a message encrypted with the new cipher spec.
9. The server sends an Encrypted Handshake Message, which contains the pre-master secret encrypted with the client's public key.
10. The client and server can now exchange application data.
TCP establishes a connection between the client and the server to guarantee the order of the packages, on the other hand, UDP does not establish a connection between the client and server and doesn't handle package orders. This makes UDP more lightweight than TCP and a perfect candidate for services like streaming.
A default gateway serves as an access point or IP router that a networked computer uses to send information to a computer in another network or the internet.
ARP stands for Address Resolution Protocol. When you try to ping an IP address on your local network, say 192.168.1.1, your system has to turn the IP address 192.168.1.1 into a MAC address. This involves using ARP to resolve the address, hence its name.
Systems keep an ARP look-up table where they store information about what IP addresses are associated with what MAC addresses. When trying to send a packet to an IP address, the system will first consult this table to see if it already knows the MAC address. If there is a value cached, ARP is not used.
- TTL (Time to Live) is a value in an IP (Internet Protocol) packet that determines how many hops or routers a packet can travel before it is discarded. Each time a packet is forwarded by a router, the TTL value is decreased by one. When the TTL value reaches zero, the packet is dropped, and an ICMP (Internet Control Message Protocol) message is sent back to the sender indicating that the packet has expired.
- TTL is used to prevent packets from circulating indefinitely in the network, which can cause congestion and degrade network performance.
- It also helps to prevent packets from being trapped in routing loops, where packets continuously travel between the same set of routers without ever reaching their destination.
- In addition, TTL can be used to help detect and prevent IP spoofing attacks, where an attacker attempts to impersonate another device on the network by using a false or fake IP address. By limiting the number of hops that a packet can travel, TTL can help prevent packets from being routed to destinations that are not legitimate.
It is possible to have two DHCP servers on the same network, however, it is not recommended, and it is important to configure them carefully to prevent conflicts and configuration problems.
- When two DHCP servers are configured on the same network, there is aĀ risk that both servers will assign IP addresses and other network configuration settings to the same device, which can cause conflicts and connectivity issues. Additionally, if the DHCP servers are configured with different network settings or options, devices on the network may receive conflicting or inconsistent configuration settings.
- However, in some cases, it may be necessary to have two DHCP servers on the same network, such as in large networks where one DHCP server may not be able to handle all the requests. In such cases, DHCP servers can be configured to serve different IP address ranges or different subnets, so they do not interfere with each other.
- SSL (Secure Sockets Layer) tunneling is a technique used to establish a secure, encrypted connection between two endpoints over an insecure network, such as the Internet. The SSL tunnel is created by encapsulating the traffic within an SSL connection, which provides confidentiality, integrity, and authentication.
2. Once the SSL session is established, the client and server negotiate encryption parameters, such as the encryption algorithm and key length, then exchange digital certificates to authenticate each other.
- A socket is a software endpoint that enables two-way communication between processes over a network. Sockets provide a standardized interface for network communication, allowing applications to send and receive data across a network. To view the list of open sockets on a Linux system:Ā
***netstat -an***
- This command displays a list of all open sockets, along with their protocol, local address, foreign address, and state.
- IPv6 (Internet Protocol version 6) is the latest version of the Internet Protocol (IP), which is used to identify and communicate with devices on a network. IPv6 addresses are 128-bit addresses and are expressed in hexadecimal notation, such as 2001:0db8:85a3:0000:0000:8a2e:0370:7334.
There are several reasons why we should consider using IPv6 over IPv4:
1. Address space: IPv4 has a limited address space, which has been exhausted in many parts of the world. IPv6 provides a much larger address space, allowing for trillions of unique IP addresses.
2. Security: IPv6 includes built-in support for IPsec, which provides end-to-end encryption and authentication for network traffic.
3. Performance: IPv6 includes features that can help to improve network performance, such as multicast routing, which allows a single packet to be sent to multiple destinations simultaneously.
4. Simplified network configuration: IPv6 includes features that can simplify network configuration, such as stateless autoconfiguration, which allows devices to automatically configure their own IPv6 addresses without the need for a DHCP server.
5. Better mobility support: IPv6 includes features that can improve mobility support, such as Mobile IPv6, which allows devices to maintain their IPv6 addresses as they move between different networks.
- A VLAN (Virtual Local Area Network) is a logical network that groups together a set of devices on a physical network, regardless of their physical location. VLANs are created by configuring network switches to assign a specific VLAN ID to frames sent by devices connected to a specific port or group of ports on the switch.
False. Ping is actually using ICMP (Internet Control Message Protocol) which is a network protocol used to send diagnostic messages and control messages related to network communication.
- SDN stands for Software-Defined Networking. It is an approach to network management that emphasizes the centralization of network control, enabling administrators to manage network behavior through a software abstraction.
- In a traditional network, network devices such as routers, switches, and firewalls are configured and managed individually, using specialized software or command-line interfaces. In contrast, SDN separates the network control plane from the data plane, allowing administrators to manage network behavior through a centralized software controller.
- ICMP stands for Internet Control Message Protocol. It is a protocol used for diagnostic and control purposes in IP networks. It is a part of the Internet Protocol suite, operating at the network layer.
ICMP messages are used for a variety of purposes, including:
1. Error reporting: ICMP messages are used to report errors that occur in the network, such as a packet that could not be delivered to its destination.
2. Ping: ICMP is used to send ping messages, which are used to test whether a host or network is reachable and to measure the round-trip time for packets.
3. Path MTU discovery: ICMP is used to discover the Maximum Transmission Unit (MTU) of a path, which is the largest packet size that can be transmitted without fragmentation.
4. Traceroute: ICMP is used by the traceroute utility to trace the path that packets take through the network.
NAT stands for Network Address Translation. Itās a way to map multiple local private addresses to a public one before transferring the information. Organizations that want multiple devices to employ a single IP address use NAT, as do most home routers.
For example, your computer's private IP could be 192.168.1.100, but your router maps the traffic to its public IP (e.g. 1.1.1.1). Any device on the internet would see the traffic coming from your public IP (1.1.1.1) instead of your private IP (192.168.1.100).
Several factors can affect network performance, including:
1. Bandwidth: The available bandwidth of a network connection can significantly impact its performance. Networks with limited bandwidth can experience slow data transfer rates, high latency, and poor responsiveness.
2. Latency: Latency refers to the delay that occurs when data is transmitted from one point in a network to another. High latency can result in slow network performance, especially for real-time applications like video conferencing and online gaming.
3. Network congestion: When too many devices are using a network at the same time, network congestion can occur, leading to slow data transfer rates and poor network performance.
4. Packet loss: Packet loss occurs when packets of data are dropped during transmission. This can result in slower network speeds and lower overall network performance.
5. Network topology: The physical layout of a network, including the placement of switches, routers, and other network devices, can impact network performance.
6. Network protocol: Different network protocols have different performance characteristics, which can impact network performance. For example, TCP is a reliable protocol that can guarantee the delivery of data, but it can also result in slower performance due to the overhead required for error checking and retransmission.
7. Network security: Security measures such as firewalls and encryption can impact network performance, especially if they require significant processing power or introduce additional latency.
8. Distance: The physical distance between devices on a network can impact network performance, especially for wireless networks where signal strength and interference can affect connectivity and data transfer rates.
OSPF (Open Shortest Path First) is a routing protocol that can be implemented on various types of routers. In general, OSPF is supported on most modern routers, including those from vendors such as Cisco, Juniper, and Huawei. The protocol is designed to work with IP-based networks, including both IPv4 and IPv6. Also, it uses a hierarchical network design, where routers are grouped into areas, with each area having its own topology map and routing table. This design helps to reduce the amount of routing information that needs to be exchanged between routers and improve network scalability.
The OSPF 4 Types of routers are:
* Internal Router
* Area Border Routers
* Autonomous Systems Boundary Routers
* Backbone Routers
Learn more about OSPF router types: https://www.educba.com/ospf-router-types/
Bandwidth is the capacity of a communication channel to measure how much data the latter can handle over a specific time period. More bandwidth would imply more traffic handling and thus more data transfer.
Network congestion occurs when there is too much data to transmit on a network and it doesn't have enough capacity to handle the demand. </br>
This can lead to increased latency and packet loss. The causes can be multiple, such as high network usage, large file transfers, malware, hardware issues, or network design problems. </br>
To prevent network congestion, it's important to monitor your network usage and implement strategies to limit or manage the demand.
HTTP Strict Transport Security is a web server directive that informs user agents and web browsers how to handle its connection through a response header sent at the very beginning and back to the browser. This forces connections over HTTPS encryption, disregarding any script's call to load any resource in that domain over HTTP.
Read more [here](https://www.globalsign.com/en/blog/what-is-hsts-and-how-do-i-use-it#:~:text=HTTP%20Strict%20Transport%20Security%20(HSTS,and%20back%20to%20the%20browser.)
"responsible for making it easy to run programs (even allowing you to seemingly run many at the same time), allowing programs to share memory, enabling programs to interact with devices, and other fun stuff like that".
* The OS is reading program's code and any additional relevant data
* Program's code is loaded into the memory or more specifically, into the address space of the process.
* Memory is allocated for program's stack (aka run-time stack). The stack also initialized by the OS with data like argv, argc and parameters to main()
* Memory is allocated for program's heap which is required for dynamically allocated data like the data structures linked lists and hash tables
* I/O initialization tasks are performed, like in Unix/Linux based systems where each process has 3 file descriptors (input, output and error)
False. It was true in the past but today's operating systems perform lazy loading which means only the relevant pieces required for the process to run are loaded first.
Even when using a system with one physical CPU, it's possible to allow multiple users to work on it and run programs. This is possible with time sharing where computing resources are shared in a way it seems to the user the system has multiple CPUs but in fact it's simply one CPU shared by applying multiprogramming and multi-tasking.
Somewhat the opposite of time sharing. While in time sharing a resource is used for a while by one entity and then the same resource can be used by another resource, in space sharing the space is shared by multiple entities but in a way where it's not being transferred between them.<br>
It's used by one entity until this entity decides to get rid of it. Take for example storage. In storage, a file is yours until you decide to delete it.
Virtual memory combines your computer's RAM with temporary space on your hard disk. When RAM runs low, virtual memory helps to move data from RAM to a space called a paging file. Moving data to paging file can free up the RAM so your computer can complete its work. In general, the more RAM your computer has, the faster the programs run.
Copy-on-write (COW) is a resource management concept, with the goal to reduce unnecessary copying of information. It is a concept which is implemented for instance within the POSIX fork syscall, which creates a duplicate process of the calling process.
1. If resources are shared between 2 or more entities (for example shared memory segments between 2 processes) the resources don't need to be copied for every entity, but rather every entity has a READ operation access permission on the shared resource. (the shared segments are marked as read-only)
(Think of every entity having a pointer to the location of the shared resource which can be dereferenced to read its value)
2. If one entity would perform a WRITE operation on a shared resource a problem would arise since the resource also would be permanently changed for ALL other entities sharing it.
(Think of a process modifying some variables on the stack, or allocatingy some data dynamically on the heap, these changes to the shared resource would also apply for ALL other processes, this is definitely an undesirable behaviour)
3. As a solution only if a WRITE operation is about to be performed on a shared resource, this resource gets COPIED first and then the changes are applied.
<summary>True or False? Some pieces of the code in the kernel are loaded into protected areas of the memory so applications can't overwritten them</summary><br><b>
Buffer: Reserved place in RAM which is used to hold data for temporary purposes
Cache: Cache is usually used when processes reading and writing to the disk to make the process faster by making similar data used by different programs easily accessible.
Virtualization uses software to create an abstraction layer over computer hardware that allows the hardware elements of a single computerāprocessors, memory, storage and more - to be divided into multiple virtual computers, commonly called virtual machines (VMs).
Red Hat: "A hypervisor is software that creates and runs virtual machines (VMs). A hypervisor, sometimes called a virtual machine monitor (VMM), isolates the hypervisor operating system and resources from the virtual machines and enables the creation and management of those VMs."
Due to having its own drivers and a direct access to hardware components, a baremetal hypervisor will often have better performances along with stability and scalability.
On the other hand, there will probably be some limitation regarding loading (any) drivers so a hosted hypervisor will usually benefit from having a better hardware compatibility.
<summary>How the introduction of virtual machines changed the industry and the way applications were deployed?</summary><br><b>
The introduction of virtual machines allowed companies to deploy multiple business applications on the same hardware while each application is separated from each other in secured way, where each is running on its own separate operating system.
Yes, virtual machines are still relevant even in the age of containers. While containers provide a lightweight and portable alternative to virtual machines, they do have certain limitations. Virtual machines still matter because they offer isolation and security, can run different operating systems, and are good for legacy apps. Containers limitations for example are sharing the host kernel.
Prometheus is a popular open-source systems monitoring and alerting toolkit, originally developed at SoundCloud. It is designed to collect and store time-series data, and to allow for querying and analysis of that data using a powerful query language called PromQL. Prometheus is frequently used to monitor cloud-native applications, microservices, and other modern infrastructure.
Some of the main features of Prometheus include:
1. Data model: Prometheus uses a flexible data model that allows users to organize and label their time-series data in a way that makes sense for their particular use case. Labels are used to identify different dimensions of the data, such as the source of the data or the environment in which it was collected.
2. Pull-based architecture: Prometheus uses a pull-based model to collect data from targets, meaning that the Prometheus server actively queries its targets for metrics data at regular intervals. This architecture is more scalable and reliable than a push-based model, which would require every target to push data to the server.
3. Time-series database: Prometheus stores all of its data in a time-series database, which allows users to perform queries over time ranges and to aggregate and analyze their data in various ways. The database is optimized for write-heavy workloads, and can handle a high volume of data with low latency.
4. Alerting: Prometheus includes a powerful alerting system that allows users to define rules based on their metrics data and to send alerts when certain conditions are met. Alerts can be sent via email, chat, or other channels, and can be customized to include specific details about the problem.
5. Visualization: Prometheus has a built-in graphing and visualization tool, called PromDash, which allows users to create custom dashboards to monitor their systems and applications. PromDash supports a variety of graph types and visualization options, and can be customized using CSS and JavaScript.
Overall, Prometheus is a powerful and flexible tool for monitoring and analyzing systems and applications, and is widely used in the industry for cloud-native monitoring and observability.
The Prometheus architecture consists of four major components:
1. Prometheus Server: The Prometheus server is responsible for collecting and storing metrics data. It has a simple built-in storage layer that allows it to store time-series data in a time-ordered database.
2. Client Libraries: Prometheus provides a range of client libraries that enable applications to expose their metrics data in a format that can be ingested by the Prometheus server. These libraries are available for a range of programming languages, including Java, Python, and Go.
3. Exporters: Exporters are software components that expose existing metrics from third-party systems and make them available for ingestion by the Prometheus server. Prometheus provides exporters for a range of popular technologies, including MySQL, PostgreSQL, and Apache.
4. Alertmanager: The Alertmanager component is responsible for processing alerts generated by the Prometheus server. It can handle alerts from multiple sources and provides a range of features for deduplicating, grouping, and routing alerts to appropriate channels.
Overall, the Prometheus architecture is designed to be highly scalable and resilient. The server and client libraries can be deployed in a distributed fashion to support monitoring across large-scale, highly dynamic environments
Compared to other monitoring solutions, such as InfluxDB, Prometheus is known for its high performance and scalability. It can handle large volumes of data and can easily be integrated with other tools in the monitoring ecosystem. InfluxDB, on the other hand, is known for its ease of use and simplicity. It has a user-friendly interface and provides easy-to-use APIs for collecting and querying data.
Another popular solution, Nagios, is a more traditional monitoring system that relies on a push-based model for collecting data. Nagios has been around for a long time and is known for its stability and reliability. However, compared to Prometheus, Nagios lacks some of the more advanced features, such as multi-dimensional data model and powerful query language.
Overall, the choice of a monitoring solution depends on the specific needs and requirements of the organization. While Prometheus is a great choice for large-scale monitoring and alerting, InfluxDB may be a better fit for smaller environments that require ease of use and simplicity. Nagios remains a solid choice for organizations that prioritize stability and reliability over advanced features.
In Prometheus, an alert is a notification triggered when a specific condition or threshold is met. Alerts can be configured to trigger when certain metrics cross a certain threshold or when specific events occur. Once an alert is triggered, it can be routed to various channels, such as email, pager, or chat, to notify relevant teams or individuals to take appropriate action. Alerts are a critical component of any monitoring system, as they allow teams to proactively detect and respond to issues before they impact users or cause system downtime.
In Prometheus, an instance refers to a single target that is being monitored. For example, a single server or service. A job is a set of instances that perform the same function, such as a set of web servers serving the same application. Jobs allow you to define and manage a group of targets together.
In essence, an instance is an individual target that Prometheus collects metrics from, while a job is a collection of similar instances that can be managed as a group.
Prometheus supports several types of metrics, including:
1. Counter: A monotonically increasing value used for tracking counts of events or samples. Examples include the number of requests processed or the total number of errors encountered.
2. Gauge: A value that can go up or down, such as CPU usage or memory usage. Unlike counters, gauge values can be arbitrary, meaning they can go up and down based on changes in the system being monitored.
3. Histogram: A set of observations or events that are divided into buckets based on their value. Histograms help in analyzing the distribution of a metric, such as request latencies or response sizes.
4. Summary: A summary is similar to a histogram, but instead of buckets, it provides a set of quantiles for the observed values. Summaries are useful for monitoring the distribution of request latencies or response sizes over time.
Prometheus also supports various functions and operators for aggregating and manipulating metrics, such as sum, max, min, and rate. These features make it a powerful tool for monitoring and alerting on system metrics.
The exporter serves as a bridge between the third-party system or application and Prometheus, making it possible for Prometheus to monitor and collect data from that system or application.
The exporter acts as a server, listening on a specific network port for requests from Prometheus to scrape metrics. It collects metrics from the third-party system or application and transforms them into a format that can be understood by Prometheus. The exporter then exposes these metrics to Prometheus via an HTTP endpoint, making them available for collection and analysis.
Exporters are commonly used to monitor various types of infrastructure components such as databases, web servers, and storage systems. For example, there are exporters available for monitoring popular databases such as MySQL and PostgreSQL, as well as web servers like Apache and Nginx.
Overall, exporters are a critical component of the Prometheus ecosystem, allowing for the monitoring of a wide range of systems and applications, and providing a high degree of flexibility and extensibility to the platform.
<summary>Which Prometheus best practices?</summary><br><b>
Here are three of them:
1. Label carefully: Careful and consistent labeling of metrics is crucial for effective querying and alerting. Labels should be clear, concise, and include all relevant information about the metric.
2. Keep metrics simple: The metrics exposed by exporters should be simple and focus on a single aspect of the system being monitored. This helps avoid confusion and ensures that the metrics are easily understandable by all members of the team.
3. Use alerting sparingly: While alerting is a powerful feature of Prometheus, it should be used sparingly and only for the most critical issues. Setting up too many alerts can lead to alert fatigue and result in important alerts being ignored. It is recommended to set up only the most important alerts and adjust the thresholds over time based on the actual frequency of alerts.
To get the total requests in a given period of time using Prometheus, you can use the *sum* function along with the *rate* function. Here is an example query that will give you the total number of requests in the last hour:
```
sum(rate(http_requests_total[1h]))
```
In this query, *http_requests_total* is the name of the metric that tracks the total number of HTTP requests, and the *rate* function calculates the per-second rate of requests over the last hour. The *sum* function then adds up all of the requests to give you the total number of requests in the last hour.
You can adjust the time range by changing the duration in the *rate* function. For example, if you wanted to get the total number of requests in the last day, you could change the function to *rate(http_requests_total[1d])*.
HA stands for High Availability. This means that the system is designed to be highly reliable and always available, even in the face of failures or other issues. In practice, this typically involves setting up multiple instances of Prometheus and ensuring that they are all synchronized and able to work together seamlessly. This can be achieved through a variety of techniques, such as load balancing, replication, and failover mechanisms. By implementing HA in Prometheus, users can ensure that their monitoring data is always available and up-to-date, even in the face of hardware or software failures, network issues, or other problems that might otherwise cause downtime or data loss.
In Prometheus, joining two metrics can be achieved using the *join()* function. The *join()* function combines two or more time series based on their label values. It takes two mandatory arguments: *on* and *table*. The on argument specifies the labels to join *on* and the *table* argument specifies the time series to join.
Here's an example of how to join two metrics using the *join()* function:
```
sum_series(
join(
on(service, instance) request_count_total,
on(service, instance) error_count_total,
)
)
```
In this example, the *join()* function combines the *request_count_total* and *error_count_total* time series based on their *service* and *instance* label values. The *sum_series()* function then calculates the sum of the resulting time series
To write a query that returns the value of a label in Prometheus, you can use the *label_values* function. The *label_values* function takes two arguments: the name of the label and the name of the metric.
For example, if you have a metric called *http_requests_total* with a label called *method*, and you want to return all the values of the *method* label, you can use the following query:
```
label_values(http_requests_total, method)
```
This will return a list of all the values for the *method* label in the *http_requests_total* metric. You can then use this list in further queries or to filter your data.
To convert *cpu_user_seconds* to CPU usage in percentage, you need to divide it by the total elapsed time and the number of CPU cores, and then multiply by 100. The formula is as follows:
```
100 * sum(rate(process_cpu_user_seconds_total{job="<job-name>"}[<time-period>])) by (instance) / (<time-period> *<num-cpu-cores>)
```
Here, *<job-name>* is the name of the job you want to query, *<time-period>* is the time range you want to query (e.g. *5m*, *1h*), and *<num-cpu-cores>* is the number of CPU cores on the machine you are querying.
For example, to get the CPU usage in percentage for the last 5 minutes for a job named *my-job* running on a machine with 4 CPU cores, you can use the following query:
```
100 * sum(rate(process_cpu_user_seconds_total{job="my-job"}[5m])) by (instance) / (5m * 4)
With <code>var x int = 2</code> we are setting the variable type to integer while with <code>x := 2</code> we are letting Go figure out by itself the type.
Go's iota identifier is used in const declarations to simplify definitions of incrementing numbers. Because it can be used in expressions, it provides a generality beyond that of simple enumerations.
<br>
`x` and `y` in the first iota group, `z` in the second.
<br>
[Iota page in Go Wiki](https://github.com/golang/go/wiki/Iota)
* There is no definitive answer to which is better, it depends on the specific use case and requirements. Some explanations : Embedded documents provide atomic updates, while referenced documents allow for better normalization.
<summary>Have you performed data retrieval optimizations in Mongo? If not, can you think about ways to optimize a slow data retrieval?</summary><br><b>
<summary>Which of the following queries would you use?
```
SELECT count(*) SELECT count(*)
FROM shawarma_purchases FROM shawarma_purchases
WHERE vs. WHERE
YEAR(purchased_at) == '2017' purchased_at >= '2017-01-01' AND
purchased_at <= '2017-31-12'
```
</summary><br><b>
```
SELECT count(*)
FROM shawarma_purchases
WHERE
purchased_at >= '2017-01-01' AND
purchased_at <= '2017-31-12'
```
When you use a function (`YEAR(purchased_at)`) it has to scan the whole database as opposed to using indexes and basically the column as it is, in its natural state.
* Management Network - used for internal communication between OpenStack components. Any IP address in this network is accessible only within the datacetner
* Guest Network - used for communication between instances/VMs
* API Network - used for services API communication. Any IP address in this network is publicly accessible
* External Network - used for public communication. Any IP address in this network is accessible by anyone on the internet
* glance-api - responsible for handling image API calls such as retrieval and storage. It consists of two APIs: 1. registry-api - responsible for internal requests 2. user API - can be accessed publicly
* glance-registry - responsible for handling image metadata requests (e.g. size, type, etc). This component is private which means it's not available publicly
* metadata definition service - API for custom metadata
* database - for storing images metadata
* image repository - for storing images. This can be a filesystem, swift object storage, HTTP, etc.
</b></details>
#### OpenStack - Swift
<details>
<summary>Explain Swift in detail</summary><br><b>
* Swift is Object Store service and is an highly available, distributed and consistent store designed for storing a lot of data
* Swift is distributing data across multiple servers while writing it to multiple disks
* One can choose to add additional servers to scale the cluster. All while swift maintaining integrity of the information and data replications.
</b></details>
<details>
<summary>Can users store by default an object of 100GB in size?</summary><br><b>
Not by default. Object Storage API limits the maximum to 5GB per object but it can be adjusted.
</b></details>
<details>
<summary>Explain the following in regards to Swift:
<summary>Explain Cinder in detail</summary><br><b>
* Cinder is OpenStack Block Storage service
* It basically provides used with storage resources they can consume with other services such as Nova
* One of the most used implementations of storage supported by Cinder is LVM
* From user perspective this is transparent which means the user doesn't know where, behind the scenes, the storage is located or what type of storage is used
* Puppet has a primary-secondary node architecture. The clients are distributed across the network and communicate with the primary-secondary environment where Puppet modules are present. The client agent sends a certificate with its ID to the server; the server then signs that certificate and sends it back to the client. This authentication allows for secure and verifiable communication between the client and the master.
* Puppet is often compared to other configuration management tools like Chef, Ansible, SaltStack, and cfengine. The choice to use Puppet often depends on an organization's needs, such as ease of use, scalability, and community support.
* Facter is a standalone tool in Puppet that collects information about a system and its configuration, such as the operating system, IP addresses, memory, and network interfaces. This information can be used in Puppet manifests to make decisions about how resources should be managed, and to customize the behavior of Puppet based on the characteristics of the system. Facter is integrated into Puppet, and its facts can be used within Puppet manifests to make decisions about resource management.
* Hiera is a hierarchical data store in Puppet that is used to separate data from code, allowing data to be more easily separated, managed, and reused.
<summary>Explain what is Elasticsearch</summary><br><b>
From the official [docs](https://www.elastic.co/guide/en/elasticsearch/reference/current/documents-indices.html):
"Elasticsearch is a distributed document store. Instead of storing information as rows of columnar data, Elasticsearch stores complex data structures that have been serialized as JSON documents"
From the [blog](https://logit.io/blog/post/the-top-50-elk-stack-and-elasticsearch-interview-questions):
"Logstash is a powerful, flexible pipeline that collects, enriches and transports data. It works as an extract, transform & load (ETL) tool for collecting log messages."
"Kibana is an open source analytics and visualization platform designed to work with Elasticsearch. You use Kibana to search, view, and interact with data stored in Elasticsearch indices. You can easily perform advanced data analysis and visualize your data in a variety of charts, tables, and maps."
<summary>Describe what happens from the moment an app logged some information until it's displayed to the user in a dashboard when the Elastic stack is used</summary><br><b>
<summary>What is Coordinating only node?</summary><br><b>
From the official docs:
Coordinating only nodes can benefit large clusters by offloading the coordinating node role from data and master-eligible nodes. They join the cluster and receive the full cluster state, like every other node, and they use the cluster state to route requests directly to the appropriate place(s).
You can choose to have one index to hold all the data of your app or have multiple indices where each index holds different type of your app (e.g. index for each service your app is running).
The official docs also offer a great explanation (in general, it's really good documentation, as every project should have):
"An index can be thought of as an optimized collection of documents and each document is a collection of fields, which are the key-value pairs that contain your data"
An index is split into shards and documents are hashed to a particular shard. Each shard may be on a different node in a cluster and each one of the shards is a self contained index.<br>
This allows Elasticsearch to scale to an entire cluster of servers.
Continuing with the comparison to SQL/NoSQL a Document in Elasticsearch is a row in table in the case of SQL or a document in a collection in the case of NoSQL.
As in NoSQL a document is a JSON object which holds data on a unit in your app. What is this unit depends on the your app. If your app related to book then each document describes a book. If you are app is about shirts then each document is a shirt.
<summary>You check the health of your elasticsearch cluster and it's red. What does it mean? What can cause the status to be yellow instead of green?</summary><br><b>
<summary>True or False? Elasticsearch indexes all data in every field and each indexed field has the same data structure for unified and quick query ability</summary><br><b>
False.
From the official docs:
"Each indexed field has a dedicated, optimized data structure. For example, text fields are stored in inverted indices, and numeric and geo fields are stored in BKD trees."
In a network/cloud environment where failures can be expected any time, it is very useful and highly recommended to have a failover mechanism in case a shard/node somehow goes offline or disappears for whatever reason.
To this end, Elasticsearch allows you to make one or more copies of your indexās shards into what are called replica shards, or replicas for short.
<summary>Can you explain Term Frequency & Document Frequency?</summary><br><b>
Term Frequency is how often a term appears in a given document and Document Frequency is how often a term appears in all documents. They both are used for determining the relevance of a term by calculating Term Frequency / Document Frequency.
<summary>What this command does? <code>curl -X PUT "localhost:9200/customer/_doc/1?pretty" -H 'Content-Type: application/json' -d'{ "name": "John Doe" }'</code></summary><br><b>
It creates customer index if it doesn't exists and adds a new document with the field name which is set to "John Dow". Also, if it's the first document it will get the ID 1.
</b></details>
<details>
<summary>What will happen if you run the previous command twice? What about running it 100 times?</code></summary><br><b>
1. If name value was different then it would update "name" to the new value
2. In any case, it bumps version field by one
</b></details>
<details>
<summary>What is the Bulk API? What would you use it for?</code></summary><br><b>
Bulk API is used when you need to index multiple documents. For high number of documents it would be significantly faster to use rather than individual requests since there are less network roundtrips.
<summary>Explain what is Relevance Score</summary><br><b>
</b></details>
<details>
<summary>Explain Query Context and Filter Context</summary><br><b>
From the official docs:
"In the query context, a query clause answers the question āHow well does this document match this query clause?ā Besides deciding whether or not the document matches, the query clause also calculates a relevance score in the _score meta-field."
"In a filter context, a query clause answers the question āDoes this document match this query clause?ā The answer is a simple Yes or Noāāāno scores are calculated. Filter context is mostly used for filtering structured data"
<summary>Describe how would an architecture of production environment with large amounts of data would be different from a small-scale environment</summary><br><b>
There are several possible answers for this question. One of them is as follows:
A small-scale architecture of elastic will consist of the elastic stack as it is. This means we will have beats, logstash, elastcsearch and kibana.<br>
A production environment with large amounts of data can include some kind of buffering component (e.g. Reddis or RabbitMQ) and also security component such as Nginx.
Filebeat is used to monitor the logging directories inside of VMs or mounted as a sidecar if exporting logs from containers, and then forward these logs onward for further processing, usually to logstash.
Filebeat is a typical component of the ELK stack, since it was developed by Elastic to work with the other products (Logstash and Kibana). It's possible to send logs directly to logstash, though this often requires coding changes for the application. Particularly for legacy applications with little test coverage, it might be a better option to use filebeat, since you don't need to make any changes to the application code.
These are pre-configured modules for specific types of logging locations (eg, Traefik, Fargate, HAProxy) to make it easy to configure forwarding logs using filebeat. They have different configurations based on where you're collecting logs from.
"Many processes running on many machines...only message-passing via an unreliable network with variable delays, and the system may suffer from partial failures, unreliable clocks, and process pauses."
<summary>What is "Shared-Nothing" architecture?</summary><br><b>
It's an architecture in which data is and retrieved from a single, non-shared, source usually exclusively connected to one node as opposed to architectures where the request can get to one of many nodes and the data will be retrieved from one shared location (storage, memory, ...).
<summary>What happens when you type in a URL in an address bar in a browser?</summary><br><b>
1. The browser searches for the record of the domain name IP address in the DNS in the following order:
* Browser cache
* Operating system cache
* The DNS server configured on the user's system (can be ISP DNS, public DNS, ...)
2. If it couldn't find a DNS record locally, a full DNS resolution is started.
3. It connects to the server using the TCP protocol
4. The browser sends an HTTP request to the server
5. The server sends an HTTP response back to the browser
6. The browser renders the response (e.g. HTML)
7. The browser then sends subsequent requests as needed to the server to get the embedded links, javascript, images in the HTML and then steps 3 to 5 are repeated.
I like this definition from [blog.christianposta.com](https://blog.christianposta.com/microservices/api-gateways-are-going-through-an-identity-crisis):
"An explicitly and purposefully defined interface designed to be invoked over a network that enables software developers to get programmatic access to data and functionality within an organization in a controlled and comfortable way."
<summary>What is an API specification?</summary><br><b>
From [swagger.io](https://swagger.io/resources/articles/difference-between-api-documentation-specification):
"An API specification provides a broad understanding of how an API behaves and how the API links with other APIs. It explains how the API functions and the results to expect when using the API"
</b></details>
<details>
<summary>True or False? API Definition is the same as API Specification</summary><br><b>
False. From [swagger.io](https://swagger.io/resources/articles/difference-between-api-documentation-specification):
"An API definition is similar to an API specification in that it provides an understanding of how an API is organized and how the API functions. But the API definition is aimed at machine consumption instead of human consumption of APIs."
An API gateway is like the gatekeeper that controls how different parts talk to each other and how information is exchanged between them.
The API gateway provides a single point of entry for all clients, and it can perform several tasks, including routing requests to the appropriate backend service, load balancing, security and authentication, rate limiting, caching, and monitoring.
By using an API gateway, organizations can simplify the management of their APIs, ensure consistent security and governance, and improve the performance and scalability of their backend services. They are also commonly used in microservices architectures, where there are many small, independent services that need to be accessed by different clients.
- Simplifies API management: Provides a single entry point for all requests, which simplifies the management and monitoring of multiple APIs.
- Improves security: Able to implement security features like authentication, authorization, and encryption to protect the backend services from unauthorized access.
- Enhances scalability: Can handle traffic spikes and distribute requests to backend services in a way that maximizes resource utilization and improves overall system performance.
- Enables service composition: Can combine different backend services into a single API, providing more granular control over the services that clients can access.
- Facilitates integration with external systems: Can be used to expose internal services to external partners or customers, making it easier to integrate with external systems and enabling new business models.
<summary>What is Automation? How it's related or different from Orchestration?</summary><br><b>
Automation is the act of automating tasks to reduce human intervention or interaction in regards to IT technology and systems.<br>
While automation focuses on a task level, Orchestration is the process of automating processes and/or workflows which consists of multiple tasks that usually across multiple systems.
<summary>Explain what is a firmware</summary><br><b>
[Wikipedia](https://en.wikipedia.org/wiki/Firmware): "In computing, firmware is a specific class of computer software that provides the low-level control for a device's specific hardware. Firmware, such as the BIOS of a personal computer, may contain basic functions of a device, and may provide hardware abstraction services to higher-level software such as operating systems."
[Avinetworks](https://avinetworks.com/glossary/layer-7/): HTTP stands for Hypertext Transfer Protocol. HTTP uses TCP port 80 to enable internet communication. It is part of the Application Layer (L7) in OSI Model.
HTTPS is a secure version of the HTTP protocol used to transfer data between a web browser and a web server. It encrypts the communication using SSL/TLS encryption to ensure that the data is private and secure.
A proxy is a server that acts as a middleman between a client device and a destination server. It can help improve privacy, security, and performance by hiding the client's IP address, filtering content, and caching frequently accessed data.
- Proxies can be used for load balancing, distributing traffic across multiple servers to help prevent server overload and improve website or application performance. They can also be used for data analysis, as they can log requests and traffic, providing useful insights into user behavior and preferences.
A reverse proxy is a type of proxy server that sits between a client and a server, but it is used to manage traffic going in the opposite direction of a traditional forward proxy. In a forward proxy, the client sends requests to the proxy server, which then forwards them to the destination server. However, in a reverse proxy, the client sends requests to the destination server, but the requests are intercepted by the reverse proxy before they reach the server.
- They're commonly used to improve web server performance, provide high availability and fault tolerance, and enhance security by preventing direct access to the back-end server. They are often used in large-scale web applications and high-traffic websites to manage and distribute requests to multiple servers, resulting in improved scalability and reliability.
<summary>When you publish a project, you usually publish it with a license. What types of licenses are you familiar with and which one do you prefer to use?</summary><br><b>
<summary>Explain what is "X-Forwarded-For"</summary><br><b>
[Wikipedia](https://en.wikipedia.org/wiki/X-Forwarded-For): "The X-Forwarded-For (XFF) HTTP header field is a common method for identifying the originating IP address of a client connecting to a web server through an HTTP proxy or load balancer."
A load balancer accepts (or denies) incoming network traffic from a client, and based on some criteria (application related, network, etc.) it distributes those communications out to servers (at least one).
* Scalability - using a load balancer, you can possibly add more servers in the backend to handle more requests/traffic from the clients, as opposed to using one server.
* Redundancy - if one server in the backend dies, the load balancer will keep forwarding the traffic/requests to the second server so users won't even notice one of the servers in the backend is down.
<summary>What are the drawbacks of round robin algorithm in load balancing?</summary><br><b>
* A simple round robin algorithm knows nothing about the load and the spec of each server it forwards the requests to. It is possible, that multiple heavy workloads requests will get to the same server while other servers will got only lightweight requests which will result in one server doing most of the work, maybe even crashing at some point because it unable to handle all the heavy workloads requests by its own.
* Each request from the client creates a whole new session. This might be a problem for certain scenarios where you would like to perform multiple operations where the server has to know about the result of operation so basically, being sort of aware of the history it has with the client. In round robin, first request might hit server X, while second request might hit server Y and ask to continue processing the data that was processed on server X already.
<summary>Explain use case for connection draining?</summary><br><b>
To ensure that a Classic Load Balancer stops sending requests to instances that are de-registering or unhealthy, while keeping the existing connections open, use connection draining. This enables the load balancer to complete in-flight requests made to instances that are de-registering or unhealthy.
The maximum timeout value can be set between 1 and 3,600 seconds on both GCP and AWS.
The Creative Commons license is a set of copyright licenses that allow creators to share their work with the public while retaining some control over how it can be used. The license was developed as a response to the restrictive standards of traditional copyright laws, which limited access of creative works. Its creators to choose the terms under which their works can be shared, distributed, and used by others. They're six main types of Creative Commons licenses, each with different levels of restrictions and permissions, the six licenses are:
* Attribution (CC BY): Allows others to distribute, remix, and build upon the work, even commercially, as long as they credit the original creator.
* Attribution-ShareAlike (CC BY-SA): Allows others to remix and build upon the work, even commercially, as long as they credit the original creator and release any new creations under the same license.
* Attribution-NoDerivs (CC BY-ND): Allows others to distribute the work, even commercially, but they cannot remix or change it in any way and must credit the original creator.
* Attribution-NonCommercial (CC BY-NC): Allows others to remix and build upon the work, but they cannot use it commercially and must credit the original creator.
* Attribution-NonCommercial-ShareAlike (CC BY-NC-SA): Allows others to remix and build upon the work, but they cannot use it commercially, must credit the original creator, and must release any new creations under the same license.
* Attribution-NonCommercial-NoDerivs (CC BY-NC-ND): Allows others to download and share the work, but they cannot use it commercially, remix or change it in any way, and must credit the original creator.
Simply stated, the Creative Commons licenses are a way for creators to share their work with the public while retaining some control over how it can be used. The licenses promote creativity, innovation, and collaboration, while also respecting the rights of creators while still encouraging the responsible use of creative works.
More information: https://creativecommons.org/licenses/
<summary>Explain the differences between copyleft and permissive licenses</summary><br><b>
In Copyleft, any derivative work must use the same licensing while in permissive licensing there are no such condition. GPL-3 is an example of copyleft license while BSD is an example of permissive license.
A memory leak is a programming error that occurs when a program fails to release memory that is no longer needed, causing the program to consume increasing amounts of memory over time.
The leaks can lead to a variety of problems, including system crashes, performance degradation, and instability. Usually occurring after failed maintenance on older systems and compatibility with new components over time.
A file system is a way for computers and other electronic devices to organize and store data files. It provides a structure that helps to organize data into files and directories, making it easier to find and manage information. A file system is crucial for providing a way to store and manage data in an organized manner.
These are only a suggestion, use them carefully. Not every interviewer will be able to answer these (or happy to) which should be perhaps a red flag warning for your regarding working in such place but that's really up to you.
Not only this will tell you what is expected from you, it will also provide big hint on the type of work you are going to do in the first months of your job.
Unit test are a software testing technique that involves systimatically breaking down a system and testing each individual part of the assembly. These tests are automated and can be run repeatedly to allow developers to catch edge case scenarios or bugs quickly while developing.
The main objective of unit tests are to verify each function is producing proper outputs given a set of inputs.
CDN (Content Delivery Network) responsible for distributing content geographically. Part of it, is what is known as edge locations, aka cache proxies, that allows users to get their content quickly due to cache features and geographical distribution.
</b></details>
<details>
<summary>Explain Multi-CDN</summary><br><b>
In single CDN, the whole content is originated from content delivery network.<br>
In multi-CDN, content is distributed across multiple different CDNs, each might be on a completely different provider/cloud.
</b></details>
<details>
<summary>What are the benefits of Multi-CDN over a single CDN?</summary><br><b>
* Resiliency: Relying on one CDN means no redundancy. With multiple CDNs you don't need to worry about your CDN being down
* Flexibility in Costs: Using one CDN enforces you to specific rates of that CDN. With multiple CDNs you can take into consideration using less expensive CDNs to deliver the content.
* Performance: With Multi-CDN there is bigger potential in choosing better locations which more close to the client asking the content
* Scale: With multiple CDNs, you can scale services to support more extreme conditions
Disaster recovery is the process of restoring critical business systems and data after a disruptive event. The goal is to minimize the impact and resume normal business activities quickly. This involves creating a plan, testing it, backing up critical data, and storing it in safe locations. In case of a disaster, the plan is then executed, backups are restored, and systems are hopefully brought back online. The recovery process may take hours or days depending on the damages of infrastructure. This makes business planning important, as a well-designed and tested disaster recovery plan can minimize the impact of a disaster and keep operations going.
<summary>What is the difference between high availability and Disaster Recovery?</summary><br><b>
[wintellect.com](https://www.wintellect.com/high-availability-vs-disaster-recovery): "High availability, simply put, is eliminating single points of failure and disaster recovery is the process of getting a system back to an operational state when a system is rendered inoperative. In essence, disaster recovery picks up when high availability fails, so HA first."
The load on the producers or consumers may be high which will then cause them to hang or crash.<br>
Instead of working in "push mode", the consumers can pull tasks only when they are ready to handle them. It can be fixed by using a streaming platform like Kafka, Kinesis, etc. This platform will make sure to handle the high load/traffic and pass tasks/messages to consumers only when the ready to get them.
Caching and databases serve different purposes and are optimized for different use cases.
Caching is used to speed up read operations by storing frequently accessed data in memory or on a fast storage medium. By keeping data close to the application, caching reduces the latency and overhead of accessing data from a slower, more distant storage system such as a database or disk.
On the other hand, databases are optimized for storing and managing persistent data. Databases are designed to handle concurrent read and write operations, enforce consistency and integrity constraints, and provide features such as indexing and querying.
A central processing unit (CPU) performs basic arithmetic, logic, controlling, and input/output (I/O) operations specified by the instructions in the program. This contrasts with external components such as main memory and I/O circuitry, and specialized processors such as graphics processing units (GPUs).
RAM (Random Access Memory) is the hardware in a computing device where the operating system (OS), application programs and data in current use are kept so they can be quickly reached by the device's processor. RAM is the main memory in a computer. It is much faster to read from and write to than other kinds of storage, such as a hard disk drive (HDD), solid-state drive (SSD) or optical drive.
A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to expedite image and video processing for display on a computer screen.
An embedded system is a computer system - a combination of a computer processor, computer memory, and input/output peripheral devicesāthat has a dedicated function within a larger mechanical or electronic system. It is embedded as part of a complete device often including electrical or electronic hardware and mechanical parts.
There are several types of storage, including hard disk drives (HDDs), solid-state drives (SSDs), and optical drives (CD/DVD/Blu-ray). Other types of storage include USB flash drives, memory cards, and network-attached storage (NAS).
<summary>What are some considerations DevOps teams should keep in mind when selecting hardware for their job?</summary><br>
Choosing the right DevOps hardware is essential for ensuring streamlined CI/CD pipelines, timely feedback loops, and consistent service availability. Here's a distilled guide on what DevOps teams should consider:
1.**Understanding Workloads**:
- **CPU**: Consider the need for multi-core or high-frequency CPUs based on your tasks.
- **RAM**: Enough memory is vital for activities like large-scale coding or intensive automation.
- **Storage**: Evaluate storage speed and capacity. SSDs might be preferable for swift operations.
2.**Expandability**:
- **Horizontal Growth**: Check if you can boost capacity by adding more devices.
- **Vertical Growth**: Determine if upgrades (like RAM, CPU) to individual machines are feasible.
3.**Connectivity Considerations**:
- **Data Transfer**: Ensure high-speed network connections for activities like code retrieval and data transfers.
- **Speed**: Aim for low-latency networks, particularly important for distributed tasks.
- **Backup Routes**: Think about having backup network routes to avoid downtimes.
4.**Consistent Uptime**:
- Plan for hardware backups like RAID configurations, backup power sources, or alternate network connections to ensure continuous service.
5.**System Compatibility**:
- Make sure your hardware aligns with your software, operating system, and intended platforms.
6.**Power Efficiency**:
- Hardware that uses energy efficiently can reduce costs in long-term, especially in large setups.
7.**Safety Measures**:
- Explore hardware-level security features, such as TPM, to enhance protection.
8.**Overseeing & Control**:
- Tools like ILOM can be beneficial for remote handling.
- Make sure the hardware can be seamlessly monitored for health and performance.
9.**Budgeting**:
- Consider both initial expenses and long-term costs when budgeting.
10.**Support & Community**:
- Choose hardware from reputable vendors known for reliable support.
- Check for available drivers, updates, and community discussions around the hardware.
11.**Planning Ahead**:
- Opt for hardware that can cater to both present and upcoming requirements.
12.**Operational Environment**:
- **Temperature Control**: Ensure cooling systems to manage heat from high-performance units.
- **Space Management**: Assess hardware size considering available rack space.
- **Reliable Power**: Factor in consistent and backup power sources.
13.**Cloud Coordination**:
- If you're leaning towards a hybrid cloud setup, focus on how local hardware will mesh with cloud resources.
14.**Life Span of Hardware**:
- Be aware of the hardware's expected duration and when you might need replacements or upgrades.
15.**Optimized for Virtualization**:
- If utilizing virtual machines or containers, ensure the hardware is compatible and optimized for such workloads.
16.**Adaptability**:
- Modular hardware allows individual component replacements, offering more flexibility.
17.**Avoiding Single Vendor Dependency**:
- Try to prevent reliance on a single vendor unless there are clear advantages.
18.**Eco-Friendly Choices**:
- Prioritize sustainably produced hardware that's energy-efficient and environmentally responsible.
In essence, DevOps teams should choose hardware that is compatible with their tasks, versatile, gives good performance, and stays within their budget. Furthermore, long-term considerations such as maintenance, potential upgrades, and compatibility with impending technological shifts must be prioritized.
<summary>What is the role of hardware in disaster recovery planning and implementation?</summary><br>
Hardware is critical in disaster recovery (DR) solutions. While the broader scope of DR includes things like standard procedures, norms, and human roles, it's the hardware that keeps business processes running smoothly. Here's an outline of how hardware works with DR:
1.**Storing Data and Ensuring Its Duplication**:
- **Backup Equipment**: Devices like tape storage, backup servers, and external HDDs keep essential data stored safely at a different location.
- **Disk Arrays**: Systems such as RAID offer a safety net. If one disk crashes, the others compensate.
2.**Alternate Systems for Recovery**:
- **Backup Servers**: These step in when the main servers falter, maintaining service flow.
- **Traffic Distributors**: Devices like load balancers share traffic across servers. If a server crashes, they reroute users to operational ones.
3.**Alternate Operation Hubs**:
- **Ready-to-use Centers**: Locations equipped and primed to take charge immediately when the main center fails.
- **Basic Facilities**: Locations with necessary equipment but lacking recent data, taking longer to activate.
- **Semi-prepped Facilities**: Locations somewhat prepared with select systems and data, taking a moderate duration to activate.
4.**Power Backup Mechanisms**:
- **Instant Power Backup**: Devices like UPS offer power during brief outages, ensuring no abrupt shutdowns.
- **Long-term Power Solutions**: Generators keep vital systems operational during extended power losses.
5.**Networking Equipment**:
- **Backup Internet Connections**: Having alternatives ensures connectivity even if one provider faces issues.
- **Secure Connection Tools**: Devices ensuring safe remote access, especially crucial during DR situations.
6.**On-site Physical Setup**:
- **Organized Housing**: Structures like racks to neatly store and manage hardware.
- **Emergency Temperature Control**: Backup cooling mechanisms to counter server overheating in HVAC malfunctions.
7.**Alternate Communication Channels**:
- **Orbit-based Phones**: Handy when regular communication methods falter.
- **Direct Communication Devices**: Devices like radios useful when primary systems are down.
8.**Protection Mechanisms**:
- **Electronic Barriers & Alert Systems**: Devices like firewalls and intrusion detection keep DR systems safeguarded.
- **Physical Entry Control**: Systems controlling entry and monitoring, ensuring only cleared personnel have access.
9.**Uniformity and Compatibility in Hardware**:
- It's simpler to manage and replace equipment in emergencies if hardware configurations are consistent and compatible.
10.**Equipment for Trials and Upkeep**:
- DR drills might use specific equipment to ensure the primary systems remain unaffected. This verifies the equipment's readiness and capacity to manage real crises.
In summary, while software and human interventions are important in disaster recovery operations, it is the hardware that provides the underlying support. It is critical for efficient disaster recovery plans to keep this hardware resilient, duplicated, and routinely assessed.
RAID is an acronym that stands for "Redundant Array of Independent Disks." It is a technique that combines numerous hard drives into a single device known as an array in order to improve performance, expand storage capacity, and/or offer redundancy to prevent data loss. RAID levels (for example, RAID 0, RAID 1, and RAID 5) provide varied benefits in terms of performance, redundancy, and storage efficiency.
A microcontroller is a small integrated circuit that controls certain tasks in an embedded system. It typically includes a CPU, memory, and input/output peripherals.
Direct memory access (DMA) is a feature of computer systems that allows certain hardware subsystems to access main system memory independently of the central processing unit (CPU).DMA enables devices to share and receive data from the main memory in a computer. It does this while still allowing the CPU to perform other tasks.
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<summary>What is a Real-Time Operating Systems?</summary><br><b>
A real-time operating system (RTOS) is an operating system (OS) for real-time computing applications that processes data and events that have critically defined time constraints. An RTOS is distinct from a time-sharing operating system, such as Unix, which manages the sharing of system resources with a scheduler, data buffers, or fixed task prioritization in a multitasking or multiprogramming environment. Processing time requirements need to be fully understood and bound rather than just kept as a minimum. All processing must occur within the defined constraints. Real-time operating systems are event-driven and preemptive, meaning the OS can monitor the relevant priority of competing tasks, and make changes to the task priority. Event-driven systems switch between tasks based on their priorities, while time-sharing systems switch the task based on clock interrupts.
DataOps seeks to reduce the end-to-end cycle time of data analytics, from the origin of ideas to the literal creation of charts, graphs and models that create value.
DataOps combines Agile development, DevOps and statistical process controls and applies them to data analytics.
<summary>What is Data Architecture?</summary><br><b>
An answer from [talend.com](https://www.talend.com/resources/what-is-data-architecture):
"Data architecture is the process of standardizing how organizations collect, store, transform, distribute, and use data. The goal is to deliver relevant data to people who need it, when they need it, and help them make sense of it."
<summary>What is Packer? What is it used for?</summary><br><b>
In general, Packer automates machine images creation.
It allows you to focus on configuration prior to deployment while making the images. This allows you start the instances much faster in most cases.
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<summary>Packer follows a "configuration->deployment" model or "deployment->configuration"?</summary><br><b>
A configuration->deployment which has some advantages like:
1. Deployment Speed - you configure once prior to deployment instead of configuring every time you deploy. This allows you to start instances/services much quicker.
2. More immutable infrastructure - with configuration->deployment it's not likely to have very different deployments since most of the configuration is done prior to the deployment. Issues like dependencies errors are handled/discovered prior to deployment in this model.
If you are looking for a way to prepare for a certain exam this is the section for you. Here you'll find a list of certificates, each references to a separate file with focused questions that will help you to prepare to the exam. Good luck :)
Thanks to all of our amazing [contributors](https://github.com/bregman-arie/devops-exercises/graphs/contributors) who make it easy for everyone to learn new things :)
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