Dynatrace - Zero to SuperHero in Production performance 2026

Set up a Google Cloud lab with a 90-day trial and $300 credit, create a Ubuntu 22 VM as a spot instance, and install the Dynatrace agent for hands-on practice.

Set up and configure a Google Cloud vm, install Docker, JDK, Python, and Git, clone a repo, and deploy the Easy Travel app with Docker Compose, preparing for Dynatrace monitoring.

Deploy and verify a travel booking app on linux using docker containers with nginx on port 9079. Access vm IP, sign in with a test account, and complete a booking.

Set up Dynatrace OneAgent on a Linux VM, deploy the monitoring agent with a token, and monitor your app and infrastructure from both classic and latest UI.

Learn how the one agent, a software, runs on virtual machines or containers and sends metrics, logs, traces, and end-user data securely to your Dynatrace SaaS account over https 443.

Explore Dynatrace OneAgent monitoring modes, including full stack, infrastructure, and discovery, and learn to select the appropriate mode for end-to-end monitoring or basic health checks.

Use Dynatrace ActiveGate to securely route agent data to your SaaS account. Enable private networks and hybrid setups with a secure gateway for reliable data transfer.

Learn to simulate real-time production problems with Dynatrace by configuring a VM, installing JDK, Maven, and Python, and triggering CPU, memory, IO, and database issues to analyze root causes.

Deploy the Dynatrace OneAgent on Windows machines, create a token, enable full stack monitoring, and install via MSI or PowerShell to monitor both Windows and Linux hosts.

Learn to monitor AWS with Dynatrace by installing an Active Gate on EC2, creating IAM roles for CloudWatch access, and using CloudFormation for a unified, cost-aware observability across clouds.

Learn to ingest AWS CloudWatch logs into Dynatrace via firehouse, using CloudFormation, API tokens, and subscription filters to ship only critical logs for combined logs and metrics.

learn how to switch from pull to push streaming by using CloudWatch metrics stream via Firehose to Dynatrace, achieving near real-time metrics and avoiding API throttling.

Learn to use Dynatrace to diagnose production problems and pinpoint high cpu usage patterns, including vm hosted apps, system processes, file and network activity, and traffic spikes.

Learn to debug CPU spikes with Dynatrace using basic and quick approaches, inspect host and process metrics, and pinpoint the root cause in the com.bank.transaction code via method hotspots.

Learn to diagnose high cpu caused by disk write activity. Correlate cpu with memory, disk, and network metrics to pinpoint the responsible process and method hotspots.

Discover how distributed tracing and profiling identify thread contention, revealing most threads locked and blocked; drill down to method hotspots to fix locking and improve end-user response times.

Proactively diagnose java memory problems and out of memory errors by analyzing heap memory, young and old generations, and garbage collection behavior in production.

Use Dynatrace memory profiling to diagnose out-of-memory errors, view flame graphs and survivor data to identify the bottom app code, then fix by dereferencing objects to enable GC.

Learn to monitor database performance with Dynatrace by installing the one agent on the host, identifying root causes of high CPU, and tracing SQL slowdowns, connections, and Postgres-specific metrics.

Enable the Postgres extension to access Postgres-specific metrics like deadlocks, uptime, and total connections, and configure the monitoring endpoint to visualize these metrics in Dynatrace dashboards.

Learn how to set up a GKE cluster from scratch, install the Dynatrace one agent, and prepare monitoring for Kubernetes.

Connect to a Google Cloud Kubernetes cluster, deploy a Spring Boot microservice via deployment YAML, and expose it with a load balancer; verify pods and services.

Set up Dynatrace OneAgent on a Kubernetes cluster with Helm, using the downloaded YAML, deploy the agent, and verify Dynatrace pods to monitor the cluster.

Dynatrace introduces three Kubernetes monitoring modes: platform monitoring, platform plus observability, and full stack, providing infra, application, or end-to-end observability with traces and logs.

Identify what platform monitoring mode can and cannot diagnose in Kubernetes troubleshooting. Use logs and events for pod pending, crash, and image lookback problems, then compare with application observability.

Enable both platform monitoring and application observability with Dynatrace, upload the DynaCube manifest, and monitor requests with waterfall and flame graphs to diagnose CPU and latency.

Explore full stack monitoring for complete Kubernetes observability with disk and network analysis, compare application and platform monitoring, and learn migration steps via simple YAML changes.

Explore migration challenges from Dynatrace to Datadog for APM monitoring, including uninstalling and reinstalling agents across hundreds of VMs, and learn how OpenTelemetry helps tackle these hurdles.

OpenTelemetry provides a vendor-neutral, open source standard agent installed once to collect metrics, logs, and traces, enabling backend swaps without changing the application.

Install the OpenTelemetry agent on VMs to collect metrics, logs, and traces and route them to Dynatrace or other backends like New Relic or Splunk, with flexible multi-endpoint support.

Deploy a simple OpenTelemetry demo app in a docker container, then enable the OpenTelemetry agent to collect metrics and logs and send them to Dynatrace for monitoring.

Combine OpenTelemetry with OneAgent to enable full-stack monitoring in Dynatrace, exporting traces, metrics, and logs from a multi-service app via the otel collector and API token.

Learn how tagging in Dynatrace organizes services and resources with labels and rules, enabling quick search and analysis of end-to-end applications, illustrated by Paytm’s SBI and HDFC monitoring.

Apply automatic tagging in Dynatrace to map hosts, services, and processes to customer names, enabling fast filtering and precise dashboards.

Create and use management zones in Dynatrace to isolate data by customer, such as SBI and HDFC, organizing hosts, services, and dashboards. Map rules and tags to control access.