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Periodic Table of DevOps Tools (Part-1)

Shiwani Sharma — Wed, 01 May 2024 09:12:22 +0000

Periodic Table of DevOps Tools

What is the DevOps Periodic Table?

It’s a framework where various DevOps tools are categorized and arranged in groups and categories based on their characteristics or roles within the DevOps methodology.

The main aim of the DevOps periodic table is to provide a visual representation that helps the DevOps teams understand the interconnected nature of DevOps practices.

In other words, it’s a grouping of DevOps tools arranged according to their abilities and costs in various categories. Some of the important and well-known DevOps tools include Jenkins, Docker, Git, Kubernetes, Puppet, Ansible, Gradle,Docker,Github etc to name a few.

The DevOps periodic table showcases the DevOps tools list across various categories ordered by their functionality and also the pricing model (Open Source, Free, Freemium, Paid, Enterprise).

Every single element in the Periodic table shows a general aspect of DevOps as like Automation, Collaboration,Continuous Integration, Monitoring, Security etc. These all elements of periodic table are merge and interact with each other to build an overall approach to DevOps (Development & IT Operational )

IMAGE CREDIT: https://www.edureka.co/blog/devops-periodic-table/

In the above image of the DevOps Periodic table, you can see that all the elements or DevOps tools are well arranged and categorized. Some of the tools here are very popular in the market, while others are less popular, but all tools have their own features that are beneficial for users.

It provides the visuals to the users that support the entire team as well the individuals to get to know the various components of DevOps and how these particle element relate to each other and this will also help to improve their practices and processes.

Classification of tools based on the DevOps Periodic table

The periodic table combines different DevOps tools from A to Z, categorizes them, and visualizes several tools. Let us try to understand the outline of different categories.

A

AIOps Tools

Loglizer
ScienceLogic
Ignio AIOps
IBM Turbonomic
Moogsoft

C

Continuous Integration (CI) Tools

These CI tools are crucial DevOps tools used for automation, testing, building, and integration. Selecting reliable integration techniques is essential to quickly identify mistakes. Some of the continuous integration tools include:

Circle CI
Jenkins
Teamcity
Bamboo
GitLab CI/CD
Travis CI

Continuous Delivery/Deployment (CD) Tools

These tools automate application deployment and delivery pipelines. These type of tools are used to automate and streamline the process of delivering software updates and change to production environment. Some of the important CD tools are:

Spinnaker
ArgoCD
Jenkins X
Harness
Drone

Configuration Management Tools

Configuration management tools play a vital role in the DevOps lifecycle, automating and managing configuration and infrastructure changes. These tools help users regulate all changes in a simple and comfortable manner. Some important configuration management tools include:

Ansible
Puppet
Chef
SaltStack
Terraform

Containerization & Orchestration

Containerization tools deploy, manage, and package applications using containers. Containerization and Orchestration tools have revolutionized the way teams build & manage the applications. They allow more flexibility, reliability & scalability just by reducing the problems arises with the traditional deployment methods. Some important containerization tools are:

Docker
Kubernetes
Rocket
Codefresh
Helm
Mesos
Rancher
GKE (Google Kubernetes Engine)
Docker Enterprise

Collaboration & Communication

These tools facilitate team collaboration, project management, and communication. They are also beneficial for individual users. Some collaboration and communication tools are:

Slack
Microsoft Teams
JIRA
Confluence

Cloud and Infrastructure Platform

These tools handle cloud resources and infrastructure. These tools permit the organization to manage, provision & scale their application and infrastructure efficiently & the consider tools like:

AWS (Amazon Web Services)
GCP (Google Cloud Platform)
Microsoft Azure

D

Deployment Tools

Capistrano
Juju
GoCD
Octopus Deploy
IBM UrbanCode Deploy
AWS CodeDeploy
DeployBot
Shippable

Database Automation Tools

DbVisualizer
pganalyze
Toad Edge
Kosli
Pachyderm
Liquibase

I

Infrastructure as Code (IAC)

These tools manage infrastructure using code. These tools in DevOps empower organization to manage infrastructure efficiently, increase the agility & automate provisioning of their operations while handing errors and improve the collaboration among development and operations teams. These IAC tools choice is often depends on the specific cloud provider or technology utilized by the organization. Some IAC tools include:

CloudFormation
Terraform
Pulumi
Ansible

L

Logging DevOps Tools

Papertrail
Scalyr
Fluentd
Sentry
Logstash
Loggly
Graylog

M

Monitoring Tools

Monitoring tools continuously track applications in the production phase, ensuring their performance and functionality. These tools are very important components for DevOps practices and provide the real time visibility into the performance, availability, & health of application and infrastructure. These tools helps the DevOps team to identify , performance and optimize system and guaranteed the experience of users. Some monitoring tools are:

Nagios
Datadog
New Relic
Grafana
Prometheus

O

Observability Tools

Datadog
Dynatrace
New Relic
Sentry
Signoz
Sumo Logic
Splunk

S

Source Code Management

The first stage of the DevOps lifecycle is source code, which provides the tools to generate and manage code. Here, tools are categorized for collaboration and performance control on source code. These categorized tools provide insights into which changes were made for improvement. Some of the important tools for source code management are as follows:

Github
Gitlab
Artfactory
Bitbucket
Compuware ISPW
Perforce Helixcore

Security and Compliance Tools

These tools ensure security and compliance throughout the DevOps lifecycle. These tool plays an important role in ensuring, privacy & regulatory compliance of systems, data and applications within an organization. Some of the tools include:

Twistlock
SonarQube
Anchore
Aqua Security

Conclusion

When someone starts learning DevOps tools and technologies, they get overwhelmed and also confused with the numerous tools that accomplished similar tasks, or nearly the same task without a clear opinion on the best toolchain and the workflow. Each one is Free to opt for and select his favourite tool from the bouquet and also market it as the best in the category.

The DevOps periodic table is a small attempt to lessen this chaos and confusion by grouping different Devops tools across various categories in an ordered alphabetic list , from A to Z.

To learn more about DevOps periodic table in detail, do connect with us and stay tuned for our upcoming blog.

The post Periodic Table of DevOps Tools (Part-1) appeared first on DevopsCurry.

Best Open Source Monitoring Options in 2021 for your Kubernetes Cluster

Namrata Joshi — Tue, 17 Nov 2020 14:24:25 +0000

Best Open-Source Monitoring Tools for Kubernetes in 2021

Best Open Source.. Monitoring an application’s current state is one of the most effective ways to anticipate problems and discover bottlenecks in a production environment. But it is also currently one of the biggest challenges faced by almost all of the software organizations across the globe. [Best Open Source]

Why Kubernetes is considered as the De facto standard for container orchestration?

Kubernetes has taken the container ecosystem by storm, and for good reasons. Kubernetes functions as the brain for your distributed container deployment. Kubernetes is a production-ready, open-source platform designed by Google’s using its accumulated experience in container orchestration.

Kubernetes has over 58K stars on GitHub & 2200+ contributors around the world. With the new ways of building & running applications, monitoring and observability strategies need to change.

Also monitoring Kubernetes, both the infrastructure platform and the running workloads, is on everyone’s checklist as we evolve beyond day zero and move into production.

What to Monitor?

We can try monitoring the following Kubernetes pod, node and cluster level metrices:

Container CPU and Memory Usage
Kubernetes Pod CPU and Memory Usage
Node CPU and Memory Usage
Namespace CPU and Memory Usage
Cluster CPU and Memory Usage
Container CPU and Memory Requests
Pod CPU and Memory Requests
Node CPU and Memory Requests
CPU and Memory Limits at Pod, Node and cluster levels
Kubernetes Resource Capacity

So here we bring for you some of the most popular Open-source monitoring tools to work with Kubernetes.

1. Prometheus 

Originally built at the sound cloud, Prometheus is a monitoring and alerting toolkit. It is quite popular in the development community. Now, it is governed by the CNCF (Cloud Native Computing Foundation). Prometheus simplifies the process of pulling numerical metrics based on a time series from a given metrics endpoint.   It has three elements: Prometheus server, Alert manager, and Exporters. Prometheus servers look after service discovery and pulling metrics from the exporters. The alert manager is responsible for setting up alert rules, analyzing the data in the Prometheus Db. It sends alert messages to multiple receivers if a certain rule is triggered. Exporters are independent containers that can be run on your target resource to generate & export metrics via metrics API.   Prometheus is developed to collect time-series data via a pull model over HTTP. Here, multiple modes are available for graph and dashboard support.

2. Grafana 

You can monitor your Kubernetes cluster’s performance using Grafana. It is mostly used for matric analysis and visualization suite. It allows creating custom dashboards using data taken from multiple sources.   The monitoring capabilities of Grafana include:

Cluster metrics: Pod, capacity/usage, memory capacity/ usage, CPU capacity/usage, Disk capacity/usage, an overview of nodes, pods, and containers. Node Metrics: CPU, memory available, Load per CPU, Read lops, write lops, %Util, network traffic/second, packets/second, error/second.
Pod/container Metrics: Memory usage, Network traffic, CPU usage, Read lops, write lops. Grafana offers an associated product called ‘LOKI’. Loki aggregates logs in Kubernetes and integrates well with the Grafana UI.

3. The ELK Stack   

The ELK or Elastic stack is one of the most popular open-source solutions for logging Kubernetes. The ELK consists of the following things:

Elastic search- scalable and well-performer. It can handle the storage and search across millions of docs.
Logstash- Aggregate and process logs and send the processed data for storage.
Kibana- It is an analysis interface to help users make sense of data.
Beats- These are the lightweight data shippers.

The enterprise version of ELK stack ships with X-pack, a set of additional tools that enables reporting, alerting, and role-based access control (RBAC). You need to use the previously mentioned enterprise version of the ELK stack to enable RBAC.

4. Fluentd 

Fluentd is governed by a cloud-native computing foundation (CNCF). It is a specialized data collector that unifies data collection & consumption. Fluentd helps to better understand & use of data.

Additionally, Fluentd offers built-in metrics and general purpose output interfaces for centralized collectors. It is quite popular among Kubernetes users to Logstash’s facilities, especially those performances-related. Fluentd is a high performing, scalable &reliable.

It is quite easy to add new inputs or outputs with very little effect on performance. It uses disks or memory for buffering and queuing to handle transmission failures or data overload. It supports multiple configuration options to ensure a more resilient data pipeline.

5. cAdvisor   

cAdvisor is used to collect, process, and export resource usage and performance information about running containers. Like other agents, cAdvisor is not deployed per Pod but on the node level. It’s a basic tool but a very useful one.  cAdvisor is built into Kubernetes and integrated into the Kubelet binary. It automatically detects every running container on a machine and collects system metrics like memory, CPU, network, etc.

cAdvisor is capable to support multiple endpoints despite having limited functionality. However, there are some cons of cAdvisor like it’s very basic, lacks analytical depth, and has limited functionalities.

6. Kubewatch

Kubewatch watches the specific Kubernetes events and pushes notifications on these events to various endpoints. In simple words, Kubewatch is the go-to tool to receive push notifications on available collaboration applications or notification channels.   Kubewatch is easy to configure and can be deployed using either helm or a custom deployment. It will take care of changes made to specific Kubernetes resources that you ask it to watch, like daemon sets, deployment, Pods, replica sets, replica controllers, services, secrets, and configuration maps.   Users need to run it in their K8s cluster, and the event notifications will be received via webhooks.

7. Kube-Ops-View

Kube-Ops-View is not exactly a monitoring tool. It can’t be used to monitor and alert on production issues, it can give you a nice operational picture of your Kubernetes clusters. It will also have a look at the different nodes deployed and their status along with different Pods running on the nodes.
Kube-Ops-View provides a common operational picture for multiple K8s clusters. It shows the capacity and resource usage for nodes and individual pods with animation. However, it is not a replacement for Kubernetes Dashboard or a monitoring solution. It simply helps the users to quickly figure out the usage metrics without doing too much hustle.

8. Jaeger

It’s an end-to-end distributed tracing solution. Jaeger is widely acknowledged by Kubernetes practitioners as monitoring and troubleshooting best practices. The brief history of Jaeger is that it was developed by Uber, inspired by OpenZipkin and Dapper, and donated to CNCF.   When a service failure occurs, you have no idea how the requests have gone from service to service over the network to complete a single business transaction. Debugging is extremely difficult in such conditions. Jaeger user tracing to enable root cause analysis, performance, and latency optimization. Jaeger is easy to use and provides a seamless user interface along with different instrumentation options.

9. Weave Scope

Weave Scope is a troubleshooting and monitoring tool for Docker and Kubernetes. It was developed by Weaveworks. Weave Scope allows you to gain operational insights into your Kubernetes clusters. It takes a few steps ahead of Kube-Ops-View by providing a much easier and nicer user interface.   It also provides the ability to manage containers and run diagnostic commands within the interface. Users can see the application, monitor the infrastructure. It is deployed on, and the relationships between the different components.   Weave Scope is an effective tool for gaining context on your deployment. The only drawback of Weave Scope is that it lacks analytical depth.

10. Kubernetes Dashboard

It’s a Web-based, UI add-on for Kubernetes clusters. Users can create and manage workloads as well as do discovery, load balancing, configuration, storage, and monitoring. Kubernetes dashboard offers numerous features and is quite useful for small clusters & for people starting to learn Kubernetes.   This tool offers different views for CPU and memory usage metrics aggregated across all nodes. This Dashboard is widely used to monitor the health status of workloads like pods, deployments, replica sets, etc. the installation process is quite easy and can be done using readymade YAML files.

11. Kube-state-metrics

Kube-state-metrics is a Kubernetes-native metrics service designed to listen to the Kubernetes. It generates metrics without any modification to Kubernetes API. Hence, users can rely on the same grade of stability as offered by Kubernetes API.   Kube-state-metrics is an extremely essay to use and is only a metrics service. It requires a few more bit and pieces to become part of a complete monitoring solution for Kubernetes.   Kube-state-metrics exports the metrics on the HTTP endpoint in a plain text format. Real-life Kubernetes practitioners recommend Kube-state-metrics if someone is struggling to use Prometheus for K8s monitoring.

Conclusion

In this blog post we have discussed the importance of Kubernetes monitoring and also outlined an extensive list of open-source monitoring tools for kubernetes. Finally choosing a tool depends on your monitoring needs and use cases. Open-source solutions have the advantage of being backed up by large communities driven to improve existing solutions.

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