Objective :
DevOps, or the collaboration between development and operations teams, is an
important component of companies today. Developing and implementing a DevOps
culture helps to focus IT results and to save time and money as the gap
between developers and IT operations teams closes. Just as the term and
culture are new, so are many of the best DevOps tools these DevOps engineers
use to do their jobs efficiently and productively. Tools are used in devops
cycle for configuration management, security, monitoring, automation and
logging .
What is the need for DevOps?
This
has many advantages like quick feedback from customers, better quality of
software etc. which in turn leads to high customer satisfaction. To
achieve this, companies are required to:
1. Increase deployment
frequency
2. Lower failure rate of
new releases
3. Shortened lead time
between fixes
4. Faster mean time to
recovery in the event of new release crashing
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Best Operating System for DevOps
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Linux
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Prerequisite
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Scripting language (Shell script
linux / Python /ruby etc..) + domain knowledge of
networking , storage , security ,data centre and respective area
..
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Best site for learning devops
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TOP Devops Technology
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Jenkins, Docker, Chef, Ansible,
Puppet, Nagios ,Git, Nagios
- Git
: Version Control System tool
- Jenkins
: Continuous Integration tool
- Selenium
: Continuous Testing tool
- Puppet,
Chef, Ansible : Configuration Management and Deployment tools
- Nagios
: Continuous Monitoring tool
- Docker
: Containerization tool
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DEVOPS Certification
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To earn
the RHCA: DevOps title you must pass these exams:
· EX270 –
Red Hat Certificate of Expertise in Container Management exam - coming soon
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Periodic-table-of-devops-tools
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Network Engineer -> DevOps Engineer
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From a personal growth
perspective, I would recommend learning scripting first. You will be able to
leverage scripting into automation in any role; you as a single individual
might be able to effect change across 100 devices in an hour, with only a few
errors. Your scripts can scale to tens of thousands, with zero errors -- so
long as you test them! Nothing scales like fail!
Using any sort of
scriping to handle repeatable network administration tasks is always a good
place to start. Whether bash, expect, python, ruby doesn't matter at first.
Eventually depending on what sort of shop you're looking for learning Puppet
or Chef for network administration will really help. They both work with
Cisco gear and I'm sure they work with other devices.
Try learning Bash first.
It's relatively easy, and most Ops people can understand it. Try to write
scripts that configure network devices. Or say, connects to all the routers
and stores a statistic and prints the results. Learn how to set up a git
repository, and how to store your scripts in it. Learn about Gitlab. How
could you use git with your networking devices? Wouldn't it be nice to have a
Time Machine view of all of your network configs? Since most configs are the
same, could you make a script that just changed parameters in a generic
config template, depending upon which device were to receive that template?
Are there tools out there that do this already? Take a look at Puppet, Chef,
and Ansible.
Server configuration management tools : Puppet, Chef,
Ansible and Salt, for example—are server configuration management tools. They
are primarily used for the provisioning and ongoing configuration
management of servers. They apply changes to
infrastructure using an “infrastructure as code” approach where the “desired
state” of infrastructure is stored in a repository—usually a source control
system—and updates are applied to managed systems to ensure they are in
compliance with the infrastructure’s “desired state.”
Changes to these systems
should be made using the config management tool interface/language, with the
automation routines normally written in Ruby or Python and configurations
exposed as properties in something like JSon or YAML. Any changes made
directly on a target server, will likely be reverted to the “desired state”
definition when the agents or systems next synchronize with the master.
They can also be used to
deploy and manage certain types of applications very effectively. This is I
believe is the route of much of the confusion, as some
organizations/applications use configuration management systems for
provisioning, infrastructure configuration and application
deployments. They normally do this by deploying system and application
changes in exactly the same way
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Cycle OF DevOps
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CODE ó
Test and build ó package your
application(Containers) ó Configuration Management
ó Release automation ó Monitor the deployment ó Respond , Learn and improve
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USE Case ( network automation , configuration management ) and
e-commerce website
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Making
the case for network automation and configuration management :
Are
you the kind of person that has to build out configurations? Maybe load OSs
on new devices or maybe perform an OS upgrade once or twice per year? Maybe
you need to quickly deploy a new change across several devices? And you wish
you had a tool that offered customization that made it relevant for your
environment.
Initial
device configuration – ever have to unbox a bunch of new gear and configure
each device individually? Maybe there was a bunch of copying and pasting
between text files during this process? Ansible can be used for “network
build automation” as Schulman likes to call it. This can be as simple as
using Ansible to create the finalized text files for you and you still load
them onto the devices or use Ansible for config building + deploying.
Deploying
configuration across one or more devices – this is when you’d want to deploy
a simple change across the network. Or maybe you just need to update one
device. It doesn’t matter – either can be done with Ansible.
Workflow
Automation – combine multiple network configurations and create custom
specific workflows by leveraging one or more playbooks and even intregrate to
workflows that include system and application changes. This is where Ansible
really starts to show its power.
Explain
with a use case where DevOps can be used in industry / real-life (e-commerce
website)
Etsy is a peer-to-peer e-commerce website
focused on handmade or vintage items and supplies, as well as unique
factory-manufactured items. Etsy struggled with slow, painful site updates
that frequently caused the site to go down. It affected sales
for millions of Etsy’s users who sold goods through online market place
and risked driving them to the competitor.
With the help of a new technical management team, Etsy transitioned from its
waterfall model, which produced four-hour full-site deployments twice weekly,
to a more agile approach. Today, it has a fully automated
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How do all these tools work together?
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Given below is a generic logical flow where everything
gets automated for seamless delivery. However, this flow may vary from
organization to organization as per the requirement.
1. Developers develop the code
and this source code is managed by Version Control System tools like Git etc.
2. Developers send this code to
the Git repository and any changes made in the code is committed to this
Repository.
3. Jenkins pulls this code from
the repository using the Git plugin and build it using tools like Ant or
Maven.
4. Configuration management
tools like puppet deploys & provisions testing environment and then
Jenkins releases this code on the test environment on which testing is done
using tools like selenium.
5. Once the code is tested,
Jenkins send it for deployment on the production server (even production
server is provisioned & maintained by tools like puppet).
6. After deployment It is
continuously monitored by tools like Nagios.
7. Docker containers provides
testing environment to test the build features.
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Cycle Unit OF Devops
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Details
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TOP TOOLS
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Code
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After you’ve written some code, there’s a
few things that need to happen before getting it into staging. Get it code
reviewed and approved, merge it into the master branch in a version control
repository, and run any local tests as needed.
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Top tools: Github, Bitbucket, Gerrit,
GitLab
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Test and build
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Now it’s time to automate
the execution of tasks related to building, testing, and releasing code.
Before the build can get deployed, it needs to undergo a number of tests to
ensure that it’s safe to push to production: unit tests, integration tests,
functional tests, acceptance tests, and more. Tests are a great way to ensure
that existing pieces of your codebase continue to function as expected when
new changes are introduced. It’s important to have tests that run
automatically whenever there’s a new pull request. This minimizes errors that
escape because of manual oversight, reduces the cost of performing reliable
tests, and exposes bugs earlier.
There are also a number
of great open source and paid tools that do useful things once the tests are
complete, like automatically picking up changes to the master and pulling
down dependencies from a repository to build new packages.
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Top tools include: Jenkins, GoCD, Maven,
CruiseControl, TravisCI, CircleCI
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Containers and Schedulers
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With the advent of Docker
and containers, teams can now easily provision lightweight, consistent, and
disposable staging and development environments without needing to spin up
new virtualized operating systems.
Containers standardize
how you package your application, improving storage capacity and flexibility,
and making it easier to make changes faster. This also enables your
application to run anywhere. In other words, things will magically behave in
production exactly as they did when you made the changes on your laptop.
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Top tools include: Docker, Kubernetes, Mesos,
Nomad
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Configuration Management
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With configuration
management, you can track changes to your infrastructure and maintain a
single source of system configuration. Look for a tool that makes it easy to
version control and make replicas of images — i.e. anything you can take a
snapshot of like a system, cloud instance, or container. The goal here is to
ensure standardized environments and consistent product performance.
Configuration management also helps you better identify issues that resulted
from changes, and simplifies autoscaling by automatically reproducing
existing servers when more capacity is needed.
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Top tools include: Chef, Ansible, Puppet, SaltStack
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Release automation
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Release automation tools
enable you to automatically deploy to production. They should include
capabilities such as automated rollbacks, copying artifacts to the host
before starting the deployment, and especially if you’re a larger
organization, agentless architecture to easily install agents and configure
firewalls at scale to your server instances.
Note that if something
passes the tests, it typically automatically gets deployed. One best practice
is to perform a canary deployment first that deploys to a subset of your
infrastructure, and if there are no errors, then do a fleet wide deploy.
A lot of teams also use
chat-based deployment workflows, using bots to deploy with simple commands,
so everyone can easily see deployment activity and learn together.
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Top tools include: Bamboo,
Puppet
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Monitor the deployment
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It can be really helpful
to have release dashboards and monitors set up that help you visualize
high-level release progress and status of requirements. It’s also key to
understand whether services are healthy and if there are any anomalies
before, during, and after a deploy. Make sure you are notified in real time
on key events that take place on your continuous integration servers so you
know if there’s a failed build, or know to hold or roll back on a deploy.
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Top tools
include: Datadog, Elastic Stack, PagerDuty
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Monitor
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Server monitoring
Server monitoring gives you an
infrastructure-level view. A lot of teams also use log aggregation to drill
down into specific issues. This type of monitoring enables you to aggregate
metrics (such as memory, CPU, system load averages, etc.) and understand the
health of your servers so that you can take action on issues, ideally before
applications — and the customers that use them — are affected.
Application
performance monitoring
Application performance monitoring1 provides
code-level visibility of the performance and availability of applications and
business services, such as your website. This makes it easy to quickly
understand performance metrics and meet service SLA’s.
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Server
Monitoring :
Top
tools include: Datadog, AWS Cloudwatch, Splunk, Nagios,
Pingdom, Solarwinds, Sensu
Application performance monitoring
Top
tools include: New Relic, Dynatrace, AppDynamics
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Respond and Learn
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Monitoring tools provide a lot of rich data,
but that data isn’t useful if it isn’t routed to the right people who can
take the right actions on an issue in real time. To minimize downtime, people
must be notified with the right information when issues are detected, have
well-defined processes around triage and prioritization, and be enabled to
engage in efficient collaboration and resolution.
When application and performance issues now
often cost thousands of dollars a minute, orchestrating the right response is
often highly stressful, but it can’t afford to be chaotic. In the
middle of a fire, you don’t want to waste half an hour pulling up a contact
directory and trying to figure out how to get the right people on a
conference bridge.
The good news is, PagerDuty automates the
end-to-end incident response process to shave time off of resolving both
major customer-impacting incidents or daily operational issues. Here at
PagerDuty, everyone from our engineering teams, support teams, security
teams, executives, and more, uses our product to orchestrate coordinated
response to IT and business disruptions. We have the flexibility to manage
on-call resources, suppress what’s not actionable, consolidate related
context, mobilize the right people and business stakeholders, and collaborate
with our preferred tools. If you can easily architect exactly what you want
your wartime response to look like, you’ll have a lot more peace of mind.
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Tools we use: PagerDuty, HipChat,
Slack, Conferencing tools
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Learn and improve
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When
wartime is over, incidents provide a crucial learning opportunity to
understand how to improve processes and systems to be more resilient. In
accordance with the CAMS pillars of DevOps (Culture,
Automation, Measurement, Sharing), it’s important to understand incident
response and system performance metrics, and facilitate open dialogue to
share successes and failures towards the goal of continuous improvement.
Look
for a solution that enables you to streamline post mortems and post mortem analysis1 for the purpose
of prioritizing action items regarding what needs to be fixed. You’ll want to
measure the success of a service relative to business goals and customer experience
metrics, with tools that help you understand product usage and customer
feedback. All of these will feed into the next sprint so that you can
accurately plan and prioritize both system and feature improvements — for
even better product, and happier customers.
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Tools
we use: PagerDuty Postmortems, Looker, Pendo, SurveyMonkey
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Important Tools
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Chef is
an extremely popular tool among DevOps engineers, and it’s easy to see why.
From IT automation to configuration management, Chef relies on recipes and
resources so you can manage unique configurations and feel secure knowing
Chef is checking your nodes and bringing them up to date for you.
Key Features:
·
Manage nodes from a single server
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Cross-platform management for Linux, Windows, Mac OS, and more
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Integrates with major cloud providers
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Premium features available
Cost:
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Essentials: FREE – manage 10,000+ nodes from a single server,
cloud integration, access to premium features with up to 25 nodes (hosting up
to 5 nodes), and 8×5 support (30 days)
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Subscription: $6/node/month – all Essentials plan features, plus
access to premium features and an account manager
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Enterprise: – Contact for a quote – all Subscription plan
features, plus access to premium features, unlimited 24×7 support, success
engineering, cookbook build coaching, and access to chef product team
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An
integrated technology suite enabling DevOps teams to build, ship, and
run distributed applications anywhere, Docker is a tool that allows users to
quickly assemble apps from components and work collaboratively. This open
platform for distributed applications is appropriate for managing containers
of an app as a single group and clustering an app’s containers to optimize
resources and provide high availability.
Key
Features:
·
Package dependencies with your apps in Docker containers to
make them portable and predictable during development, testing, and
deployment
·
Works with any stack
·
Isolates apps in containers to eliminate conflicts and enhance
security
·
Streamline DevOps collaboration to get features and fixes into
production more quickly
Cost:
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Community Edition: FREE
·
Enterprise Edition Basic: Starting at $750/year
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Enterprise Edition Standard: Starting at $1,500/year
·
Enterprise Edition Advanced: Starting at $2,000/year
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Providing
the simplest way to automate IT, Ansible is a DevOps tool for automating your
entire application lifecycle. Ansible is designed for collaboration and makes
it much easier for DevOps teams to scale automation, manage complex
deployments, and speed productivity.
Key
Features:
·
Deploy apps
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Manage systems
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Avoid complexity
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Simple IT automation that eliminates repetitive tasks and
frees teams to do more strategic work
Cost: Contact
for a quote
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Puppet
Enterprise is one of the most popular DevOps tools on the market because it
enables teams to deliver technology changes quickly, release better software,
and do it more frequently with confidence. Use Puppet Enterprise to manage
infrastructure as code and get a solid foundation for versioning, automated
testing, and continuous delivery.
Key
Features:
·
Deploy changes with confidence
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Recover more quickly from failures
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Free your team to be more agile and responsive to business
needs
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Increase reliability by decreasing cycle times
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Ensures consistency across development, test, and production
environments so teams know that changes are consistent and systems are stable
when you promote them
Cost: FREE
trial available
·
12-Month Puppet Enterprise Subscription for up to 500 Nodes:
$3,000 – Standard support and maintenance
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Contact sales for more than 500 nodes or for premium support
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As a version control system
(VCS) tool, Git helps developers manage their
projects with speed and efficiency. It’s free and open-source, which means
anyone can use it. One of its signature features is a branching model that allows developers
to create multiple local branches, or pointers to a commit, that are
independent of one another. Developers can then merge, create, or delete
these branches as their infrastructure evolves.
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An
extensible continuous integration engine, Jenkins is a top tool for DevOps
engineers who want to monitor executions of repeated jobs. With Jenkins,
DevOps engineers have an easier time integrating changes to projects and have
access to outputs to easily notice when something goes wrong.
Key Features:
·
Permanent links
·
RSS/email/IM integration
·
After-the-fact tagging
·
JUnit/TestNG test reporting
·
Distributed builds
Cost: FREE
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Reference
URL :
Building
a more agile, automated organization with DevOps
Top DevOps Tools: 50 Reliable, Secure,
and Proven Tools for All Your DevOps Needs
Top DevOps Questions
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