Private corporate batches, live online cohorts and 1-on-1 mentoring in dashboards, panels, variables and alerting across every time-series data source you already run — 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 Grafana as a query and presentation layer rather than a gallery of panel types — how each data source's query editor maps to its native language, when to use a transformation instead of another query, and how variables, repeats and field overrides turn one dashboard into a view of an entire estate. Sessions go through to the operational half: unified alerting with notification policies, LDAP, OAuth and SAML authentication with team sync, dashboard and data source permissions, provisioning dashboards as code, and running Grafana in high availability.
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 Grafana that means a trainer who has run it in production — dashboards, panels, variables and alerting across every time-series data source you already run — 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 Grafana batchGrafana is an open-source visualisation and analytics platform for time-series and operational data. It does not store data itself. Instead it connects to the systems that do — Prometheus, InfluxDB, Elasticsearch, Loki, Graphite, PostgreSQL, MySQL, Microsoft SQL Server, CloudWatch, Azure Monitor, Google Cloud Monitoring, Jaeger, Tempo and Zipkin among them — issues queries in each source's native language, and renders the results as panels on a dashboard.
That separation is the point. Because Grafana is a query and presentation layer rather than a database, one dashboard can mix a PromQL query, a SQL query and a Lucene query on the same screen, and a team can adopt it without migrating any of the data it already collects. Panels carry their own queries, transformations, field overrides and thresholds; dashboards carry variables that turn a single definition into a view of any environment, cluster or service.
Beyond dashboards, Grafana provides Explore for ad-hoc investigation, unified alerting with its own rule engine and notification policies, annotations that mark deploys and incidents on every graph, and an administration surface that matters once more than one team uses it: organisations and folders, dashboard and data source permissions, LDAP, OAuth and SAML authentication, team sync, provisioning as code, image rendering, plugins and high-availability deployment.
Every organisation with more than one monitoring system ends up with a visualisation problem. Metrics live in Prometheus, logs in Elasticsearch or Loki, business data in Postgres, cloud service metrics in CloudWatch — and nobody can answer a cross-cutting question without opening four tabs. Grafana exists to collapse that, and it has become the default answer because it treats every source as a first-class citizen rather than requiring a migration.
The skill gap is not in drawing a graph. It is in everything around it: designing dashboards that survive being handed to on-call, using variables and repeated rows so one dashboard serves fifty services, applying transformations instead of writing three queries, setting thresholds and field overrides that make a problem visible at a glance, and provisioning the whole lot as code so dashboards are reviewed and versioned rather than hand-edited in production.
Grafana is also where the governance conversation lands. Once dashboards drive on-call decisions, authentication, permissions, alert routing and audit stop being optional — and those are the parts teams typically discover late, after the dashboards are already load-bearing.
The architecture and the boundary. Grafana as a stateless query and presentation layer over data sources it does not own, what lives in its own database, how it compares with Kibana, Chronograf and vendor dashboards, and the honest limitations that decide whether it fits a given problem.
Topics: What Grafana is and why teams adopt it · Grafana architecture: server, data sources, its own database · Advantages and limitations of the query-layer model · Grafana compared with Kibana, Chronograf and vendor consoles · OSS, Enterprise and Cloud editions — what differs · Core vocabulary: data source, panel, dashboard, folder, organisation
Getting a server running the way you will actually run it. Package installs on Debian and RPM systems, Windows and macOS, and the Docker image with its configuration model. Then grafana.ini: the settings that matter, environment-variable overrides, the backing database, and a safe upgrade path.
Topics: Requirements and sizing · Install on Debian/Ubuntu and RPM-based Linux · Install on Windows and macOS · Running the Grafana Docker image and configuring it by environment variable · grafana.ini structure and precedence · Backing database: SQLite, MySQL, PostgreSQL · Upgrading Grafana safely and rolling back · grafana-cli and plugin installation
Connecting Grafana to the systems that hold the data, and understanding each query editor as a front end to a different language. Prometheus and PromQL, SQL sources and the macro system, Elasticsearch and Lucene, Loki and LogQL, InfluxDB, and the cloud provider sources with their own authentication models.
Topics: Adding a data source: connection, auth, TLS, default settings · Prometheus: query editor, exemplars, recording rules · PostgreSQL and MySQL: the time macros, $__timeFilter, table vs time-series format · Microsoft SQL Server and OpenTSDB · Elasticsearch: index patterns, Lucene queries, metric and bucket aggregations · InfluxDB with InfluxQL and Flux · Loki for logs and the metrics/logs split · AWS CloudWatch, Azure Monitor and Google Cloud Monitoring authentication · Tracing sources: Jaeger, Tempo, Zipkin · Graphite and the TestData source for building without real data
The unit of a dashboard. The panel editor in depth, choosing a visualisation that matches the question, multiple queries on one panel, calculations and reductions, thresholds, units, and the field options and overrides that let one panel treat one series differently from the rest.
Topics: Adding a panel and navigating the panel editor · Queries, query options, min interval and max data points · Visualisation types: time series, stat, gauge, bar gauge, table, heatmap, histogram, logs, node graph · The calculations list and reduce options · Thresholds and colour modes · Field options, units and value mappings · Overrides: targeting fields by name, type or regex · Panel inspect: data, stats, JSON and query · Sharing and embedding query results
The layer between query and visualisation. Transformations reshape results in the browser — joining, filtering, renaming, grouping, calculating fields — and remove a whole class of duplicated queries. Alongside them, the time-series concepts that decide whether a graph is truthful: dimensions, intervals, alignment, histograms and heatmaps.
Topics: Time series and time-series dimensions · Histograms and heatmaps: when each is the honest visualisation · Transformations: reduce, filter, organise fields, join by field · Add field from calculation, group by, series to rows · Chaining transformations and debugging the output · Interval alignment and the max data points trade-off · Sharing query results between panels · Grafana glossary and terminology
Assembling panels into something people use. Dashboard structure and folders, time range controls and refresh, Explore for ad-hoc investigation and the split view that pairs metrics with logs, annotations that mark deploys and incidents, playlists for wall displays, and version history and sharing.
Topics: Dashboard layout, rows and folders · Time range controls, relative ranges and refresh intervals · Explore: ad-hoc queries, split view, metrics-to-logs correlation · Annotations: manual, query-driven and region annotations · Playlists and kiosk mode for wall displays · Search, tags and keyboard shortcuts · Dashboard version history and diffing · Share dashboard, share panel, snapshots and public links · Export and import; the dashboard JSON model · Reporting and export to PDF
How one dashboard becomes fifty. Variable types and syntax, query-driven variables that populate from the data source, multi-value and All handling, regex filtering, chained variables, and repeated panels and rows. Then linking: dashboard links, panel links, data links and URL variables that carry context between views.
Topics: Variable syntax and interpolation · Variable types: query, custom, constant, datasource, interval, textbox, ad-hoc filters · Selection options: multi-value, include All, and the formatting that follows · Filtering variables with regex · Advanced variable format options for different query languages · Chained and dependent variables · Repeating panels and rows · Dashboard links, panel links and data links · URL variables and deep-linking with preserved context
Grafana's own alerting engine, distinct from the alerting built into any given data source. Alert rules and their evaluation model, the query-plus-condition structure, notification policies and routing, contact points, silences and mute timings, and how to keep alert volume defensible.
Topics: Grafana unified alerting: architecture and evaluation · Creating alert rules: query, reduce, threshold, no-data and error handling · Evaluation groups, intervals and the pending period · Labels, annotations and templating alert messages · Notification policies and routing trees · Contact points: email, Slack, PagerDuty, webhook, Opsgenie · Silences, mute timings and pausing a rule · Viewing alert state and history · Troubleshooting alerts that never fire or never clear · Where Grafana alerting overlaps with Alertmanager, and how to choose
Who gets in, and as whom. Grafana's built-in authentication, then the enterprise integrations: auth proxy, LDAP with enhanced group mapping, OAuth2 against Google, Azure AD, GitHub, GitLab and Okta, and SAML. Then user and team management, and the permission model that spans organisations, folders, dashboards and data sources.
Topics: Authentication overview and the order of providers · Grafana built-in authentication and anonymous access · Auth proxy and reverse-proxy authentication · LDAP authentication and enhanced LDAP group mapping · OAuth2: Google, Azure AD, GitHub, GitLab, Okta · SAML authentication · Team sync from the identity provider · Managing users: add, remove, enable, disable · Teams: creation, membership, and team-based access · Organisation roles: Viewer, Editor, Admin · Dashboard and folder permissions · Data source permissions
Running Grafana as infrastructure rather than an application someone installed. Provisioning data sources, dashboards and alert rules from files, the CLI and internal metrics, image rendering, security settings, server stats, plugin management and signatures, and a high-availability deployment with a shared database.
Topics: Provisioning data sources, dashboards, folders and alert rules from YAML · Storing dashboards in Git and deploying them through CI · Grafana CLI in depth · Image rendering service and why panels render blank without it · Internal Grafana metrics and self-monitoring · Jaeger instrumentation of Grafana itself · Security configuration: cookies, CSRF, content security policy, secret key · View server settings and server stats · Default home dashboard, preferences and branding basics · Plugins: installing, signatures and unsigned plugin policy · Setting up Grafana for high availability · Backup and restore
What the commercial edition adds and whether you need it, plus how Grafana fits the rest of the observability stack. Licensing and expiry behaviour, enterprise data source permissions, auditing, usage insights, Vault integration, white-labelling and PDF export — then Loki, Tempo and the correlation story across metrics, logs and traces.
Topics: Grafana Enterprise: what it adds over OSS · Licensing and license expiration behaviour · Enterprise data source permissions · Enterprise configuration options · Auditing and audit log destinations · Usage insights: which dashboards are actually used · HashiCorp Vault integration for configuration secrets · White-labelling and custom branding · Export dashboard as PDF · Correlating metrics, logs and traces with Prometheus, Loki and Tempo
We rebuild the agenda around the tools you actually run.
Request a custom agendaConnect Prometheus, a SQL database, Elasticsearch, Loki and CloudWatch, then build a single dashboard that answers one question using all five.
Take a 30-panel dashboard, cut it to the panels that drive decisions, and apply thresholds, units, overrides and transformations so a problem is visible in two seconds.
Convert a per-service dashboard into a variable-driven one with chained variables, repeated rows, regex filtering and a working drill-down path.
Build Grafana alert rules with correct no-data and error handling, route them through notification policies to different contact points, then silence a planned maintenance window.
Wire Grafana to OAuth or LDAP, sync groups to teams, and prove that a viewer in one team cannot reach another team's folder or data source.
Provision data sources, folders, dashboards and alert rules entirely from files, deploy them through CI, then destroy and rebuild the instance to prove it.
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
I recently did a SRE Session with Rajesh Kumar from DevOps School and the session was great. Right from 1st day till day 15, we had a very interactive session. Rajesh clarified our doubts and the tool demos were excellent without any hiccups. He simplified the concepts while sticking to the content with a fine balance between theory and practice. Am convinced he is one of the best trainers for SRE & DevOps concepts.
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.
Basics explanation was exemplary from Rajesh where he dealt with complicated topics to be simple. Great learning stuff personally for me.
Good discussion, helped us to understand different tools in SRE.
Very detailed explanation and has lots of patience in attending the questionnaire. Thanks again for your wonderful sessions.
| 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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