Private corporate batches, live online cohorts and 1-on-1 mentoring in the deployment pipeline that keeps every change releasable — artefact promotion, environments, data change and release evidence — taught by a practitioner who runs it in production.
20 years across DevOps, SRE and Security · 10,000+ engineers trained · Trained teams at JPMorgan Chase, Verizon, Nokia and the World Bank
Principal DevOps Engineer & Architect
Rajesh teaches Continuous Delivery around the deployment pipeline as an architecture: one artefact built once and promoted, environments provisioned from code, configuration and secrets externalised per environment, and acceptance, performance and security stages that produce evidence against the same build. Sessions go deep on the parts that stall real programmes — backward-compatible database change with expand and contract, staging environments that actually resemble production, and generating audit-acceptable release records from pipeline data instead of from a change form. Twenty years across DevOps, SRE and Security and 10,000+ engineers trained inform the trade-off calls on stage ordering, approval placement and what is worth automating first.
Twenty years across DevOps, SRE and Security, in principal and architect roles at PayPay, SoftwareAG, ServiceNow, JDA Software, Intuit, Adobe and others. He has trained engineers at JPMorgan Chase, Verizon, Nokia, the World Bank, VMware, Oracle, Mercedes-Benz and Airbus — more than 10,000 people personally. He teaches what he runs, not what he reads.
You are booked with a named engineer, and that is who turns up. Marketplaces and larger providers rotate whoever is free, so the person who sold you the agenda is rarely the person teaching it.
The same trainer is available for the next engagement, which matters when a team builds on what it learned last time.
Your batch is assigned a named trainer before it starts, and that is who teaches it. See the full faculty.
Engagements are matched on the tool, not the calendar. For Continuous Delivery that means a trainer who has run it in production — the deployment pipeline that keeps every change releasable — artefact promotion, environments, data change and release evidence — rather than whoever is free that week. You are told who is teaching before you commit, and that person is on the discovery call that shapes the agenda.
Where a batch is large enough to need a second trainer, the pairing is declared up front. The lead trainer stays accountable for the syllabus and the assessment either way.
Principal DevOps Engineer & Architect
Twenty years across DevOps, SRE and Security in principal and architect roles at PayPay, SoftwareAG, ServiceNow, JDA Software, Intuit, Adobe, IBM/Emptoris, Ness, MindTree and Accenture. He has trained more than 10,000 engineers personally, at organisations including JPMorgan Chase, Verizon, Nokia, the World Bank, VMware, Oracle, Mercedes-Benz and Airbus. He teaches what he runs, not what he reads.
Teams of 8–30
Custom agenda, your timezone, onsite or online, NDA-friendly.
Request a quoteIndividual engineers
A private instructor and a curriculum built around your goal.
₹99,999Individuals who want peers
Scheduled batch, max 8 to 10 hours of live instruction.
₹34,999A private batch starts with a discovery call. We look at the stack you actually run — the CI system, the cloud, the constraints — and map the agenda onto it, so examples use your topology rather than a generic one.
Delivery is onsite at your premises, live online, or hybrid, scheduled around your release calendar rather than ours. Batches run 8 to 30 engineers.
Every attendee leaves with recordings, slides, lab repositories and a completion certificate. You receive an attendance and assessment report. Invoicing supports PO and GST.
Talk to us about a private Continuous Delivery batchContinuous Delivery is the practice of keeping software in a state where any version that has passed the pipeline could be released to production at any moment, on a business decision rather than an engineering one. The release itself stays a choice; what stops being a choice is whether the software is ready. If a build has gone green through every stage, the only thing standing between it and users is someone deciding to press the button.
The organising structure is the deployment pipeline. A change enters once, produces exactly one versioned artefact, and that artefact is promoted through progressively more expensive and more production-like stages — automated acceptance testing, performance and capacity validation, security checks, exploratory testing — with every stage recording evidence against the same build. Nothing is rebuilt between stages; if it were, the thing tested would not be the thing released. Environments are provisioned from code so they can be recreated identically, configuration is externalised so one artefact runs everywhere, and database changes are made backward compatible so schema and code can move independently.
Continuous Delivery is where release governance is usually decided too. Instead of a committee reviewing an intention to change, the pipeline produces the evidence — what was built from which commit, what tests passed, who approved, what was deployed where and when — as a by-product of doing the work. That is what allows an organisation to release frequently and still satisfy audit, and it is the part of the practice that takes longest to get right in a regulated environment.
The gap most organisations are stuck in is between 'the build is green' and 'we could ship this today'. The code is integrated and unit tested, and then a release still takes a two-week hardening period, a staging environment that never matches production, a manually run database script, and a spreadsheet of configuration differences. Every one of those is a Continuous Delivery problem rather than a Continuous Integration problem.
It is also the practice with the clearest commercial argument. Batch size is the dominant driver of deployment risk: a release containing three months of changes fails more often and is harder to diagnose than thirty releases of one change each. Shortening the path from artefact to production reduces both lead time and change failure rate simultaneously, which is why delivery performance research keeps finding the two move together rather than trading off.
Demand has also shifted toward the hard parts. Building a pipeline that runs tests is a solved problem with good tooling. Making environments genuinely reproducible, decoupling database change from deployment, managing configuration and secrets per environment, and producing release evidence auditors accept — those are where projects stall, and they are what organisations pay a specialist to fix.
Continuous Delivery's central structure. Why a pipeline is designed rather than accumulated: stage ordering by cost and probability of failure, fan-in and fan-out, what each stage is allowed to conclude, and the difference between a pipeline that verifies releasability and one that merely runs jobs in sequence.
Topics: Releasable at all times: what the practice actually claims · Deployment pipeline anatomy from commit to production · Ordering stages by feedback cost and failure probability · Fan-out for parallel verification, fan-in for promotion · Where Continuous Integration ends and Continuous Delivery begins · Manual stages that are choices, not bottlenecks · Pipeline anti-patterns: rebuilds, environment-specific builds, snowflake stages
The rule that makes everything else possible: build once, promote the identical binary. Versioning schemes and traceability back to a commit, artefact repositories and container registries, promotion between repositories as a record of confidence, and supply chain integrity through signing and provenance.
Topics: Immutable artefacts and why rebuilding invalidates testing · Versioning schemes and traceability to source · Artefact repositories: Artifactory, Nexus, container registries · Promotion models and repository-per-stage · Dependency management and reproducible resolution · SBOM generation, artefact signing and provenance · Retention, cleanup and storage economics
The second most common cause of 'it worked in staging'. Provisioning environments from code so they can be recreated identically, achieving parity that matters while accepting the differences that do not, and externalising configuration and secrets so one artefact behaves correctly everywhere.
Topics: Environments provisioned from code with Terraform and Ansible · Environment parity: what must match and what need not · Ephemeral and on-demand environments per branch or release · Externalised configuration and the twelve-factor position · Configuration as code and drift detection · Secrets management per environment with Vault or a cloud KMS · Test data provisioning and refresh
The stages that convert 'it builds' into 'it is releasable'. Automated acceptance testing against a deployed instance, capacity and performance validation with meaningful thresholds, and the security stages — dynamic scanning, dependency and licence checks — placed where they inform a release decision rather than block one arbitrarily.
Topics: Automated acceptance testing against a deployed artefact · Writing acceptance criteria that survive UI change · Performance and capacity stages, thresholds and baselining · Load profiles that reflect real traffic · DAST, dependency and licence scanning in the pipeline · Exploratory and manual testing as a pipeline stage, not a phase · Deciding what constitutes a release verdict
The subject that stops more Continuous Delivery programmes than any other. Versioned, automated schema migration; expand and contract so that schema and application code never have to deploy together; handling large data migrations without a maintenance window; and rollback when the data has already moved.
Topics: Schema change under version control with Flyway or Liquibase · Expand and contract: adding, backfilling, switching, removing · Backward and forward compatibility between code and schema · Large data migrations without downtime · Rollback strategy when data has changed · Testing migrations against production-scale data · Stateful services, caches and message schemas
Releasing frequently and passing audit at the same time. Separating deployment from release, approvals expressed as data rather than meetings, segregation of duties inside an automated pipeline, and generating the change record from pipeline evidence so compliance is a by-product of the work.
Topics: Deployment versus release as distinct decisions · Release planning, cadence and coordinated multi-service releases · Approvals as pipeline data: who, what, when, against which artefact · Segregation of duties in an automated pipeline · Generating change records and audit evidence automatically · Working with change enablement and CAB processes · Release notes, traceability and defect linkage
Treating the pipeline as a product with users and performance characteristics. Measuring lead time, deployment frequency, change failure rate and time to restore; finding the real constraint rather than the annoying one; and the economics of pipeline investment — where automation pays back and where it does not.
Topics: Lead time, deployment frequency, change failure rate, restore time · Instrumenting a pipeline to produce those measures automatically · Finding the constraint: queue time versus processing time · Batch size and its effect on failure rate · Pipeline cost, runtime economics and compute spend · Reliability of the pipeline itself and its own error budget · Sequencing an improvement roadmap
We rebuild the agenda around the tools you actually run.
Request a custom agendaBuild a pipeline that takes a single versioned artefact from commit through acceptance, performance and security stages to a production-like environment, with no rebuild at any point.
Provision two environments from the same code, diff them systematically, eliminate the differences that matter and document the ones that do not — then destroy and rebuild both.
Take an application with environment-specific builds and rework it so a single artefact runs in dev, test, staging and production using externalised configuration and managed secrets.
Take a change that renames a column and split it into an expand-and-contract sequence deployed across four releases, with the application remaining compatible at every step.
Generate a complete, auditable release record — source commit, build inputs, test results, approvals, deployment targets and timestamps — automatically, with no manually completed form.
Deliver a pipeline for a real service where any green build could go to production, then demonstrate it by releasing three consecutive builds and reporting the measured lead time for each.
Billed yearly at ₹9,996
Max 8 to 10 hours of live instruction
Full program, private instructor
8–30 engineers · custom agenda · onsite or online · PO and GST invoicing
Refunds. If we cancel or postpone a cohort, you get a full refund within 15 days. There is no money-back guarantee otherwise.
Terms. Course material remains licensed to the attendee. Read the terms.
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Certificate of completion
Helped to understand more on overall DevOps concepts.
Got good lab sessions which kept the new DevOps tool learnings to the point and it helped a lot in my career.
Great learning experience from a very knowledgeable instructor with well-prepared course notes. The lab exercises on AWS instance work well to learn the hands-on side of the course.
Rajesh is a very good trainer I have experienced in DevSecOps training. The number of contents in different topics he has posted on the DevOpsSchool public website are amazing and user friendly for beginners and experienced professionals.
The trainer (Rajesh) provided very good sessions on SRE profession. Not only hands-on learning on the tools but also SRE mindset.
Very good training session. Well explained from the basics to the complex concepts. Also tried to cover practicals and demos within the 3 hour sessions. The learning content and videos are of a great deal of help.
| What matters | YouTube + blogs | Generic online course | Freelance marketplace | DevOpsSchool |
|---|---|---|---|---|
| Named practitioner | No | Rarely | Varies per booking | Yes — same trainer each time |
| Production experience | Unknown | Unknown | Unverified | 20 years, named employers |
| Custom agenda | No | No | Sometimes | Built from your stack |
| Onsite delivery | No | No | Sometimes | Yes |
| Lab environment | None | Sandbox that expires | Varies | Your own cloud — skill goes with you |
| Assessment | None | Quiz | Rarely | Assignments + capstone per module |
| Per-attendee certificates | No | Sometimes | Rarely | Yes |
| Corporate invoicing | No | Limited | Varies | PO and GST |
| Post-training support | None | Forum, time-limited | None | Lifetime forum access |
Tell us the team, the stack and the timeline. You'll get a straight answer, not a sales sequence.
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