DevOps Troubleshooting: Planning and Implementing a DevOps Strategy

Level: Intermediate — DevOps Practitioners, Architects, IT Managers

Table of Contents

• 1. Course Overview
• 2. Auditing Your Current State
• 3. Starting Your DevOps Pilot
• 4. Developing and Sustaining DevOps Momentum
• 5. Reference Diagrams
• 6. Reference Tables

1. Course Overview

This course covers planning and implementing an end-to-end DevOps strategy: how to start a DevOps program in your organization, how to prove value via a pilot, and how to scale DevOps to become the company’s standard way of working.

Learning Objectives

2. Auditing Your Current State

2.1 Defining DevOps

Two key definitions:

Google Cloud:

“DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders.”

Amazon Web Services:

“DevOps is the combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity.”

DevOps has its roots in Lean Manufacturing — optimizing the value flow to the customer by eliminating waste. It is not just about tools; it’s a culture change.

2.2 What NOT to Do

Six pitfalls that can sabotage your DevOps effort from the start:

2.3 Analyzing Organizational Maturity

Where to Look

1. Declared goals — OKRs, KPIs, annual reports

   • Growth in new markets?
   • Protecting existing business?
   • Cost reduction?
   • Customer retention vs. emerging competitors?

2. Business opportunities and challenges

   • Who is your main competitor? How are they doing?
   • Integrating a recently acquired company?
   • Major system end-of-life with uncertain ROI?

3. Capacity for change

   • What change management process is in place?
   • What budget is available for transformation?

2.4 Analyzing Teams and Skills

Identifying Internal Champions

A DevOps champion must:

• Have air cover — executive support
• Be respected and influential in the organization
• Be a team player who rallies, not a “polarizing genius”
• Ideally, not be limited to IT — champions can come from business

Executive sponsors: at least one IT/business leader must actively support the initiative.

Evaluating Current Skills

2.5 Analyzing Value Streams

Definition

A value stream is a specific sequence of activities required to deliver value to a customer (internal or external).

Value Stream Mapping is a technique to visualize, analyze, and improve the workflow for delivering a product or service.

Where to Focus DevOps Efforts

How to Map a Value Stream

1. Identify the trigger — What starts the work? (customer request, ticket, feature request)
2. Map the steps — From idea to production
3. Measure time — Processing time vs. wait time at each step
4. Identify bottlenecks — Where does work accumulate?
5. Calculate flow efficiency — Ratio of value time / total time

3. Starting Your DevOps Pilot

3.1 DevOps Adoption Challenges

The 6 main challenges you will encounter:

3.2 The Adoption Journey

flowchart LR
    A[Define goals\nand skill gaps] --> B[Identify\nvalue streams]
    B --> C[Launch Pilot\n5-9 people]
    C --> D[Automate\ninfrastructure]
    D --> E[Automate\napp delivery]
    E --> F[Improve\noperations]
    F --> G[Scale to\nother teams]
    G --> H[DevOps as\nstandard way of work]

3.3 What to Prove in Your Pilot

1. Measurable Impact via Customer Satisfaction

• Success metrics are not the number of servers provisioned
• They must be customer-oriented: error rates, response time, NPS, feature adoption

2. Product Teams Can Regularly Deploy to Production with Automation

• Prove the ability to automate the path to production
• Measure reduction in change failures
• Show improvement in bug fix rate

3. Sustainable Cultural Improvement is Possible

• Prove that shared metrics, blameless post-mortems, and shared ownership are viable

3.4 Building the First Team

Team Topologies Options

Team size: 5 to 9 people — small enough to move fast, large enough to cover skills. Include Dev, Ops, QA, possibly Security.

3.5 Small Batches, Visual Systems, and Continuous Delivery

Small Batches — The Secret of DevOps

flowchart TD
    A[Large annual\nrelease] --> B{If problem?}
    B --> C[LARGE impact surface\nComplex troubleshooting\nDifficult rollback]

    D[Small batch\none feature] --> E{If problem?}
    E --> F[SMALL impact surface\nCause quickly identifiable\nFast iteration possible]

Advantages of small batches:

• Fast learning — if it’s not what was wanted, you know quickly
• Limited impact if issues arise
• Shortened feedback loop
• Continuous deployment possible

Visual Systems — Making Work Visible

• Kanban boards: visualize what’s in progress, what’s blocked
• Burndown charts: sprint progression
• Production dashboards: real-time metrics visible to the whole team

Transparency breaks silos and builds a culture of trust.

3.6 Version Control: DevOps Foundation

Version control is the anchor of all DevOps practices.

Why trunk-based development?

• Without it, continuous integration is impossible
• Avoids “merge hell” — branches diverging for weeks
• Keeps the main branch almost always deployable

3.7 The Integration and Delivery Pipeline

flowchart LR
    A[Idea /\nUser Story] --> B[Version\nControl]
    B --> C[Build]
    C --> D[Automated\nTests]
    D --> E[Artifact\nManagement]
    E --> F[Deploy\nDev/QA]
    F --> G[Approval]
    G --> H[Production]

3.8 Automation to Introduce in the Pilot

3.9 Building Momentum and Visibility

• Internal forums — share what you’re learning with other teams
• Documentation — wiki, best practices accessible to all
• Visible metrics — large screens with pipeline and delivery metrics
• Identify the next team that will adopt DevOps
• Document successes AND failures — both are useful

4. Developing and Sustaining DevOps Momentum

4.1 Scaling Challenges

4.2 Expanding the Stakeholder Pool

• The average CIO tenure is ~18 months — DevOps can’t rely on one person
• Beyond IT — find champions in business lines
• Align IT VPs — VP of Ops and VP of Engineering must share the same goals
• Evangelize adjacent teams — software teams, support, architecture

4.3 Skills to Scale

Making Work Visible (Scaling)

This practice must become universal — work in progress visible by all, backlogs, burndowns, production metrics accessible to everyone.

Agile + Small Batches at Scale

Common problem observed:

Teams work in small batches, but a release team takes all those small lots and deploys them quarterly. This breaks the entire model.

Small batches must apply throughout the pipeline all the way to production.

4.4 Technology and Process Standardization

Standardize only after the pilot, never before.

Standardize on things that facilitate rotation of people between teams.

4.5 Building Subsequent Teams

• Seeding from the pilot — pilot team members temporarily or permanently join new teams
• Look for smart and motivated people for change
• Deliberate rotation propagates practices and culture

4.6 The Platform Team

Why a Platform Team?

A Platform Team solves the scaling problem by offering:

• Self-service and programmable infrastructure and delivery services
• A platform that product teams use to deploy and operate their services
• An internal product with developers as customers

flowchart TD
    PT[Platform Team\nPlatform as product] --> |Self-service APIs| P1[Product Team A]
    PT --> |Self-service APIs| P2[Product Team B]
    PT --> |Self-service APIs| P3[Product Team C]

    P1 --> |Deploy via platform| PROD[Production]
    P2 --> |Deploy via platform| PROD
    P3 --> |Deploy via platform| PROD

    P1 -.->|Feedback| PT
    P2 -.->|Feedback| PT

4.7 Shift Left on Security

“Shift left is the practice of implementing testing, security, or other development practices early in the software development lifecycle rather than at the end.” — CNCF

flowchart LR
    subgraph SL ["Shift Left"]
        SL1[SAST\nStatic Analysis]
        SL2[Dependency\nScanning]
        SL3[Secret\nDetection]
        SL4[IaC\nScanning]
    end

    subgraph SDLC ["SDLC"]
        direction LR
        A[Code] --> B[Build] --> C[Test] --> D[Deploy] --> E[Operate]
    end

    subgraph SR ["Shift Right"]
        SR1[WAF]
        SR2[DDoS Protection]
        SR3[Runtime Scan]
        SR4[Pen Testing]
    end

    SL -.->|integrated in| SDLC
    SDLC -.->|protected by| SR

4.8 IT Role Evolution

4.9 Publishing Metrics to Stakeholders

Choosing the Right Metrics

DevOps metrics are not:

• Number of servers under management
• Number of tickets closed
• Uptime percentage of an internal service

DevOps metrics are:

• Customer uptime improvement
• New customer sign-ups
• Mobile transaction latency
• Deployment frequency
• Bug fix time

Establish the Baseline

You can’t show improvement without knowing where you started.

1. Measure current state before starting
2. Document and share the baseline with stakeholders
3. Define improvement objectives
4. Track and publish regularly

4.10 Maintaining Long-Term Success

• Communities of practice — regular knowledge sharing sessions
• Internal conferences — DevOps days, workshops
• Metrics dashboards — visible and regularly updated
• Retrospectives — systematically incorporate lessons learned
• Champion rotation — don’t let all knowledge concentrate in one person

5. Reference Diagrams

5.1 DevOps Roadmap

gantt
    title DevOps Adoption Journey
    dateFormat  X
    axisFormat  Phase %s

    section Audit
    Current state analysis       :done, 1, 2

    section Pilot
    Team formation + basics      :done, 2, 3
    CI/CD + version control      :done, 3, 4
    IaC + monitoring             :done, 4, 5

    section Scaling
    Second team onboarding       :done, 5, 6
    Platform team creation       :done, 6, 7
    Shift left security          :done, 7, 8

    section Maturity
    DORA metrics + optimization  :done, 8, 9
    DevOps as standard           :done, 9, 10

5.2 Organizational Transformation

flowchart TD
    subgraph Before ["Before DevOps"]
        DEV_B[Dev Team] --> RELEASE_B[Release Team]
        RELEASE_B --> OPS_B[Ops Team]
        OPS_B --> PROD_B[Production]
        DEV_B x--x OPS_B
    end

    subgraph After ["After DevOps"]
        DEV_A[Dev + Ops\nCross-functional team] --> PIPE_A[Automated Pipeline]
        PIPE_A --> PROD_A[Production]
        PLATFORM[Platform Team\nSelf-service] --> DEV_A
    end

6. Reference Tables

6.1 Key DevOps Metrics (DORA)

6.2 Team Topologies

6.3 Frameworks and Tools by Domain

6.4 DevOps Maturity Levels

Recommended Resources

Essential Books

Annual Reports

• DORA State of DevOps Report — Google Cloud annual report on DevOps state
• GitLab DevSecOps Survey — Global DevSecOps trends

Search Terms

devops · troubleshooting · planning · strategy · ci/cd · git · team · analyzing · batches · metrics · pilot · skills · teams · adoption · automation · challenges · current · delivery · maturity · momentum · organizational · platform · reference · scale