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High Availability in DevOps

High Availability in DevOps

$302.00
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What does the High Availability in DevOps course cover?

High Availability in DevOps is covered here in 9 modules: Defining High Availability Requirements and SLIs, Infrastructure Design for Fault Tolerance, Automated Deployment and Immutable Infrastructure and 6 more. The outline lists 72 specific topics, opening with selecting appropriate service level indicators (SLIs) such as request latency, error rate, and throughput based on user-facing impact and closing with aligning backup retention schedules.

How do you approach High Availability in DevOps step by step?

The work is sequenced in 9 stages. It starts with Defining High Availability Requirements and SLIs, moves through Infrastructure Design for Fault Tolerance and Automated Deployment and Immutable Infrastructure, and ends at Security and Compliance in High Availability Systems. Each stage carries its own topic list, so the sequence is followed rather than summarised.

What is in Module 1 of the High Availability in DevOps course?

Module 1 is Defining High Availability Requirements and SLIs. It works through selecting appropriate service level indicators (SLIs) such as request latency, error rate, and throughput based on user-facing impact, negotiating SLOs with product and operations stakeholders to balance business needs with technical feasibility, mapping user journeys to identify critical paths that require high availability protection and 5 more.

How is the High Availability in DevOps course delivered?

The High Availability in DevOps course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the High Availability in DevOps course cost?

The High Availability in DevOps course is $300 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

Closely related courses: High Availability in Availability Management, High Availability Toolkit, High Availability Environment Toolkit, DevOps with Docker, Kubernetes, and AWS.

More answers: what you get with every course, refund policy, all help answers.

This curriculum spans the design, deployment, and operational lifecycle of highly available systems, comparable in scope to a multi-workshop reliability engineering program implemented across large-scale cloud environments.

Module 1: Defining High Availability Requirements and SLIs

  • Selecting appropriate service level indicators (SLIs) such as request latency, error rate, and throughput based on user-facing impact
  • Negotiating SLOs with product and operations stakeholders to balance business needs with technical feasibility
  • Mapping user journeys to identify critical paths that require high availability protection
  • Determining acceptable downtime windows for non-critical subsystems during maintenance
  • Implementing synthetic monitoring to simulate user behavior for accurate SLI measurement
  • Configuring error budgets to guide release velocity and incident response priorities
  • Documenting recovery time objectives (RTO) and recovery point objectives (RPO) for each service tier
  • Establishing escalation thresholds based on SLO burn rate detection

Module 2: Infrastructure Design for Fault Tolerance

  • Distributing workloads across multiple availability zones to mitigate zone-level failures
  • Selecting instance types with appropriate burst capacity and redundancy for stateful services
  • Designing multi-region architectures for disaster recovery with data replication strategies
  • Implementing anti-affinity rules to prevent co-location of redundant instances
  • Configuring resilient storage backends using distributed file systems or managed databases
  • Validating failover mechanisms through controlled zone evacuation drills
  • Choosing between active-passive and active-active topologies based on cost and complexity trade-offs
  • Integrating hardware health checks with orchestration layers for automatic node replacement

Module 3: Automated Deployment and Immutable Infrastructure

  • Enforcing immutable server patterns using container images or golden AMIs to reduce configuration drift
  • Implementing blue-green or canary deployments with traffic shifting via service mesh or load balancer
  • Automating rollback triggers based on SLO violations during deployment windows
  • Validating deployment artifacts with static analysis and vulnerability scanning in CI pipeline
  • Managing configuration secrets using encrypted parameter stores with least-privilege access
  • Synchronizing infrastructure changes across regions using declarative templates
  • Enforcing deployment freeze policies during high-risk periods using pipeline guards
  • Instrumenting deployment metadata to correlate incidents with recent changes

Module 4: Resilient Service Communication

  • Implementing circuit breakers and bulkheads in service clients to prevent cascading failures
  • Configuring retry budgets with exponential backoff and jitter for transient errors
  • Enforcing service-to-service authentication using mTLS in a service mesh
  • Setting timeout budgets that align with upstream and downstream SLOs
  • Routing traffic around degraded services using health-aware load balancing
  • Managing DNS TTL values to balance caching efficiency with failover responsiveness
  • Implementing graceful degradation of non-essential features during partial outages
  • Monitoring and alerting on increased latency or error rates in inter-service calls

Module 5: Data Consistency and Replication

  • Selecting replication topology (synchronous vs asynchronous) based on RPO and latency tolerance
  • Configuring quorum-based consensus in distributed databases for write availability
  • Handling split-brain scenarios with automated fencing and leader election
  • Maintaining referential integrity across sharded databases during failover
  • Implementing change data capture for cross-region data synchronization
  • Validating data consistency using checksums and reconciliation jobs
  • Planning for backward and forward compatibility in schema migrations
  • Testing backup restoration procedures with point-in-time recovery

Module 6: Monitoring, Alerting, and Observability

  • Defining actionable alerts based on symptoms (e.g., latency, errors) rather than causes
  • Reducing alert fatigue by grouping related signals and setting proper thresholds
  • Instrumenting distributed traces to diagnose latency bottlenecks across services
  • Correlating logs, metrics, and traces using unique request identifiers
  • Setting up golden signal dashboards for real-time service health visibility
  • Automating alert routing to on-call engineers using escalation policies
  • Validating monitoring coverage through fault injection and chaos engineering
  • Archiving telemetry data according to retention policies and compliance requirements

Module 7: Incident Response and Postmortem Culture

  • Activating incident response protocols with defined roles (incident commander, comms lead)
  • Using communication bridges and status pages to coordinate internal and external updates
  • Executing predefined runbooks for common failure scenarios
  • Preserving system state and logs during incidents for forensic analysis
  • Conducting blameless postmortems with root cause analysis and action item tracking
  • Integrating postmortem findings into reliability improvements and training materials
  • Testing incident response readiness through simulated outage drills
  • Managing executive and stakeholder communication during major incidents

Module 8: Capacity Planning and Load Management

  • Forecasting resource demand using historical growth trends and business projections
  • Implementing auto-scaling policies based on queue depth, CPU, or custom metrics
  • Setting scaling limits to prevent runaway costs during traffic spikes
  • Simulating traffic surges using load testing tools to validate scaling behavior
  • Implementing rate limiting and quota enforcement at API gateways
  • Using priority queuing to protect core functionality during overload
  • Pre-warming infrastructure ahead of scheduled high-traffic events
  • Monitoring for resource exhaustion in shared pools (e.g., database connections)

Module 9: Security and Compliance in High Availability Systems

  • Integrating security patching into automated deployment pipelines without downtime
  • Enforcing encryption at rest and in transit across all data tiers
  • Implementing audit logging with immutable storage for compliance verification
  • Designing secure cross-region data transfer to meet data sovereignty requirements
  • Validating failover configurations against security policy enforcement points
  • Conducting penetration testing on disaster recovery environments
  • Managing access keys and certificates with automated rotation and revocation
  • Aligning backup retention schedules with regulatory data preservation mandates
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