An SRE does not need to master every programming language. The goal is to become strong enough at programming to automate operational work, build reliable tooling, troubleshoot production systems, and understand how applications behave in production.
Google describes SRE as treating operations as a software engineering problem, so programming is an important part of the role rather than an optional skill.
1. Python — The Best Starting Point
Python is probably the best first programming language for most SREs.
It is useful for:
- Automation scripts
- API integrations
- Monitoring tools
- Log processing
- Incident-response automation
- Cloud automation
- Infrastructure tooling
- Data processing
- Testing
For example, an SRE might write a Python script that checks the health of hundreds of services and automatically creates an incident when a critical condition is detected.
Python is also useful because SREs frequently need to modify or troubleshoot automation quickly during operational incidents. Google has documented historical SRE tooling written in Python specifically because its quick development and modification characteristics were useful in production environments.
2. Go — Extremely Valuable for Modern SRE
Go (Golang) is another language worth learning, particularly for SREs working with cloud-native infrastructure.
Go is widely used for infrastructure and distributed systems because it provides good performance, concurrency support, straightforward deployment, and a strong ecosystem for cloud tooling.
Google's SRE training material specifically notes that more projects were being created in Go, particularly in SRE, making Go an important language for many SREs.
Go is particularly useful when working with technologies such as:
- Kubernetes
- Cloud-native tooling
- Networking services
- Distributed systems
- CLI tools
- Infrastructure components
- High-performance services
You don't necessarily need Go on day one. A good approach is to learn Python first and then add Go when your role or projects require it.
3. Bash/Shell — Essential for Infrastructure Work
Even though Bash is not normally considered a general-purpose application-development language, SREs should be comfortable with shell scripting.
Bash is useful for:
- Linux administration
- Process management
- File manipulation
- Log analysis
- Deployment scripts
- Cron jobs
- Troubleshooting
- CI/CD automation
- Running infrastructure commands
For example:
kubectl get pods
docker ps
grep "ERROR" application.log
systemctl status nginx
An SRE may combine commands like these into automation scripts.
However, Bash should generally be used for relatively small utilities and straightforward scripts. Google's shell guidance recommends moving longer or complicated scripts into a more structured programming language.
4. Java — Useful When Supporting Java Applications
Java isn't mandatory for every SRE, but it can be extremely useful if the organization runs Java-based applications.
Understanding Java helps an SRE investigate issues such as:
- JVM memory usage
- Garbage collection
- Thread problems
- Application crashes
- CPU spikes
- Connection-pool issues
- Performance bottlenecks
For example, if a Java application repeatedly experiences OutOfMemoryError, an SRE who understands the JVM can investigate heap usage, garbage collection, thread behavior, and application-level causes more effectively.
Google's release-engineering documentation lists Java alongside Python, Go, C++, and JavaScript among languages supported in its build environment.
5. JavaScript/TypeScript — Useful for Web and Platform Systems
JavaScript or TypeScript can be valuable when an SRE supports:
- Node.js applications
- Web platforms
- Serverless applications
- Internal developer portals
- APIs
- Frontend infrastructure
- Infrastructure dashboards
You don't necessarily need deep frontend expertise, but understanding the runtime, package ecosystem, HTTP behavior, and common failure modes can be helpful when supporting modern web applications.
6. SQL — Don't Ignore It
SQL is extremely useful for SREs, even though it isn't a general-purpose programming language.
Production incidents frequently involve databases.
An SRE may need to investigate:
- Slow queries
- Connection exhaustion
- Lock contention
- Replication problems
- Missing indexes
- Unexpected data growth
- Database resource utilization
For example:
SELECT COUNT(*)
FROM orders
WHERE created_at >= CURRENT_DATE;
Being comfortable with SQL allows an SRE to investigate application and database behavior without always depending on a database specialist.
7. C/C++ — Useful for Specialized SRE Roles
C or C++ is not required for most SRE positions.
However, it becomes valuable when working close to:
- Operating systems
- Kernels
- Networking
- High-performance systems
- Storage systems
- Infrastructure software
- Low-level debugging
An SRE working on large-scale infrastructure may eventually encounter problems that require understanding memory management, system calls, CPU behavior, or native libraries.
For a beginner, however, I would put C/C++ much lower on the learning priority list than Python, Bash, and Go.
Which Languages Should an SRE Learn First?
I would recommend this order:
1. Python — Automation and general SRE tooling
2. Bash — Linux and operational scripting
3. Go — Cloud-native and infrastructure engineering
4. SQL — Database troubleshooting
5. Java/JavaScript/TypeScript — Based on the application stack
6. C/C++ — For specialized low-level systems work
The exact order should change depending on the environment. There is no universal requirement that every SRE learn the same languages.
Programming Skills Matter More Than Language Count
One common mistake is thinking:
“I know five programming languages, so I'm ready for SRE.”
That's not necessarily true.
An SRE should focus on problem-solving and automation rather than collecting programming languages.
For example, you should be able to write a program that:
- Reads monitoring data.
- Detects an abnormal condition.
- Calls an API.
- Collects additional diagnostics.
- Generates a useful incident report.
- Performs a safe remediation action when appropriate.
- Logs what happened.
That demonstrates much more relevant SRE ability than simply knowing the syntax of several languages.
Learn Programming Alongside SRE Concepts
Programming should be learned together with core SRE concepts such as:
- Linux
- Networking
- Distributed systems
- Monitoring
- Observability
- Incident response
- SLOs and SLIs
- Error budgets
- Capacity planning
- Automation
- CI/CD
- Cloud platforms
- Kubernetes
Google's SRE Workbook identifies SLOs, monitoring, alerting, eliminating toil, and simplicity as foundational SRE practices.
So programming should support these skills rather than become a separate learning goal.
A Practical SRE Programming Roadmap
A beginner could follow something like:
Linux fundamentals
↓
Bash scripting
↓
Python automation
↓
Git + CI/CD
↓
Cloud APIs and automation
↓
SQL and database troubleshooting
↓
Kubernetes
↓
Go
↓
Distributed systems and reliability engineering
At every stage, build small projects.
For example:
Python Project:
Create a script that checks API health and sends an alert when latency exceeds a threshold.
Bash Project:
Create a log-analysis script that identifies repeated application errors.
Go Project:
Build a simple HTTP health-check or metrics service.
SQL Project:
Analyze database queries and identify slow or abnormal patterns.
These projects help connect programming skills directly to SRE responsibilities.
Final Thoughts
For most SREs, Python + Bash + Go + SQL is an excellent core combination.
Python is great for automation and tooling, Bash is essential for Linux operations, Go is highly valuable for cloud-native infrastructure, and SQL is important for troubleshooting databases.
After that, learn the language used by the applications you support.
The most important thing is not to become a programmer who happens to work in operations. The goal is to become an engineer who can use software to solve operational problems at scale.
That is very close to the fundamental SRE philosophy: use engineering and automation to reduce manual operational work and make systems more reliable.