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Phase 1. Where to start
Why this course exists and who it fits: the problem it solves, how phases, quizzes, tests and trainers work, and how to go through it without dropping off.
- Зачем этот курс required
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Phase 2. Language basics: Go · 19 questions
Syntax, structs and methods, interfaces, slices and maps, errors, goroutines and channels, pointers, tooling — language foundations before backend plumbing.
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Phase 3. Algorithms and data structures · 44 questions
Arrays and Big-O, sorting, stacks and queues, lists, recursion, trees, hash tables, heaps and graphs — the foundation under collections, indexes and stores.
- Why data structures and algorithms matter
- Math behind big O: logarithms, powers and growth rates required
- Arrays and binary search: big-O notation, ArrayList and Arrays.binarySearch required
- Simple sorting: bubble, selection, insertion required
- Stacks and queues: LIFO, FIFO, circular queue and ArrayDeque
- Linked Lists: Nodes, References and Why LinkedList Loses to ArrayList
- Recursion: base case, call stack and divide and conquer required
- Advanced sorting: Shell sort, quicksort and radix sort
- Binary search trees: the rule, traversal, deletion and TreeMap
- Red-black trees: rotations, recoloring and TreeMap
- 2-3-4 trees and B-trees: multi-key nodes and database indexes
- Hash tables: hash function, collisions and load factor required
- Heaps: weak ordering, sift up and sift down, PriorityQueue
- Graphs: vertices, edges, DFS and BFS
- Weighted graphs: minimum spanning tree and shortest path
- Two pointers and the sliding window required
- Prefix sums: a range sum as the difference of two numbers required
- Binary search on the answer: monotonicity, bounds and the loop invariant required
- Monotonic stack: next greater element in a single pass required
- Dynamic programming: overlapping subproblems, memoisation and tables required
- Backtracking: the search tree, undoing state, pruning dead branches required
- Choosing a data structure: array, list, tree or hash table required
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 4. Git and branching models · 27 questions
Snapshots and commits, branches and merging, push/pull, pull requests and code review, rebase and reflog, branching models from Git Flow to trunk-based.
- What Git is and why everyone needs it required
- Commits and history: add, commit, log, and .gitignore required
- Branches and merging: merge and conflicts required
- Remote repositories: push, pull, and fetch required
- Pull requests and code review required
- Rebase and cherry-pick: rewriting history
- Undo and recovery: reset, revert, reflog
- Branching models: Git Flow, GitHub Flow, trunk-based
- Phase test in the cabinet
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Phase 5. Go as the foundation · 19 questions
The core Go stack: structure and wiring, chi and net/http, JSON, validation, middleware, context, errors, sqlc+pgx, concurrency.
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Phase 6. SQL from scratch · 46 questions
The query language before any particular database: tables and keys, SELECT and WHERE, joins, aggregates, NULL, subqueries, window functions, dates and strings, modifying data, creating tables and why a query suddenly got slow.
- What a Database and Tables Are required
- SELECT: Pick, Filter, Sort required
- JOIN: Combine Data from Several Tables required
- Aggregates: COUNT, GROUP BY and HAVING required
- NULL and Data Types: Where Everyone Stumbles required
- Subqueries and CTEs: A Query Inside a Query required
- Window Functions: Counting Without Collapsing Rows
- Даты и время
- Строки
- INSERT, UPDATE, DELETE and Transactions required
- Database Schema: Tables, Keys and Views
- Why a Query Is Slow: Indexes on Your Fingers required
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 7. Data: PostgreSQL · 19 questions
Relational fundamentals: ACID and isolation levels, partitioning and sharding.
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Phase 8. Other stores: documents, search, files, analytics · 135 questions
First the foundations — storage engines, replication, sharding, streams. Then the stores themselves: MongoDB, Elasticsearch, object storage (S3) and ClickHouse for specialized workloads.
- B-trees and LSM-trees in plain words: how a database stores data required
- OLTP and OLAP in plain words: two different worlds of working with data required
- Schema evolution in plain words: changing data formats without breaking anything
- Replication models in plain words: why a replica lags, multi-leader, and quorums required
- Partitioning (sharding) in plain words: slicing data across nodes without a hot spot required
- System of record and derived data in plain words: why a cache, an index, and a read model are the same thing
- Stream processing in plain words: change data capture (CDC) and time in streams
- ACID, read and write concerns, transactions in MongoDB in Go
- Replication and Sharding in MongoDB
- Document modeling in MongoDB: embed vs reference, indexes required
- Elasticsearch: how a search engine works required
- How Queries Work in Elasticsearch and Why Documents Are Ranked the Way They Are required
- How Elasticsearch works in production: ILM, snapshots, sizing, monitoring
- What object storage is: bucket, object, key, storage classes and presigned URL required
- S3 in production: backups, replication, cost, and monitoring
- How ClickHouse Works: Columnar Storage, MergeTree, and OLAP required
- ClickHouse: schema modeling, queries, materialized views required
- ClickHouse in production: replication, TTL, backups and monitoring
- Cassandra Architecture: a Ring With No Leader Node
- Cassandra Data Model: Partition Key and Clustering Columns
- Consistency and Replication in Cassandra: Tunable per Request
- How Neo4j Works: the Property Graph, Nodes, Relationships and Index-Free Traversal
- Cypher: a Graph Query Language in Plain Words
- Neo4j graph modeling: indexes, supernodes and operations
- PostgreSQL or MongoDB: how to choose a database
- Oracle or PostgreSQL: differences and migration
- Cassandra, PostgreSQL or MongoDB: when to reach for a wide-column NoSQL
- Graph data in plain words: recursive SQL or a graph database
- Neo4j: применение
- PostgreSQL or ClickHouse: when to add a second database
- Search: PostgreSQL FTS or Elasticsearch
- Files: in the database or in object storage
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 9. Design principles and patterns · 28 questions
SOLID, GoF, GRASP and the DRY/KISS/YAGNI principles with examples.
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Phase 10. Networking fundamentals · 44 questions
OSI and TCP/IP models, IP and ports, TCP/UDP, DNS, HTTP and HTTPS, HTTP versions, connections and reliability.
- How Networking Works: The OSI and TCP/IP Models required
- IP Addresses, Ports, and NAT
- TCP and UDP: Reliability vs Speed required
- DNS: How a Domain Name Turns Into an Address required
- HTTP: Methods, Status Codes, Headers required
- HTTPS and TLS: Encryption and the Handshake required
- HTTP/1.1, HTTP/2, and HTTP/3: What Changed
- Connections: Keep-Alive, Pools, and Timeouts
- Два пула: БД и HTTP
- Load Balancers and Reverse Proxies required
- Networking and Reliability: Timeouts, Retries, Idempotency
- Диагностика сети
- WebSocket, SSE and long polling required
- WebSocket: много подов
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 11. API: REST and contracts · 49 questions
REST contracts in Go: URLs and resources, parameters, responses, errors, versioning, OpenAPI.
- URLs and Resources in a Go REST API — kebab-case, Nesting, chi
- Query Parameters — Filtering, Pagination, Sorting in Go
- JSON and Response Format in a Go REST API
- REST API Errors in Go — RFC 9457, ProblemDetails, Validation
- HTTP headers in Go: standard, custom, and tracing
- REST API Versioning in Go: /api/v1 and breaking changes
- Alias and Action Endpoints in Go — me, latest, and Domain Commands
- OpenAPI and Common Mistakes in REST APIs on Go
- Rate limiting, files, deprecation in a Go REST API
- Batch operations, long-running tasks and error localization in Go
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 12. Security and authorization · 25 questions
Auth in Go and authorization patterns: where checks live, JWT, RBAC/ABAC, secrets and auditing.
- Аутентификация
- Authentication and authorization patterns
- Which Check Goes Where — Gateway, BFF, and Domain Service (Go)
- JWT validation in Go: golang-jwt and JWKS
- RBAC in Go: Roles from JWT and Checking in chi Middleware
- ABAC and Resource Ownership in Go
- Storing Tokens on the Client — HttpOnly Cookies and Refresh Rotation (Go)
- Service-to-Service Authentication in Go — mTLS and Client Credentials
- PII and Secrets in Go — What Must Not Go into slog, error, and Kafka
- Administrator Action Journal in Go
- PCI DSS for developers
- GDPR for Developers
- Phase test in the cabinet
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Phase 13. Brokers and distributed systems · 37 questions
AMQP/RabbitMQ, Kafka and distributed patterns: saga, outbox, idempotency.
- The AMQP protocol: exchange, queue, binding, ack required
- RabbitMQ in production: clustering, queue types and monitoring
- Messaging Patterns with AMQP in Go
- AMQP vs Kafka: which broker to choose required
- Apache Kafka: topics, partitions, ordering and guarantees in Go
- Kafka in production in Go: kafka-go, DLQ, Schema Registry, tuning, security
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 14. Microservices: architecture and pitfalls · 32 questions
Whether you need microservices, how a service is structured and how they communicate; what breaks in a distributed system and how to fix it — saga, outbox, idempotency, resilience.
- Choosing your starting architecture: monolith, modular monolith, microservices required
- Structural Patterns for Microservices in Go
- Between services: synchronous call or events required
- The trouble with distributed systems in plain words: partial failures, unreliable clocks, truth by quorum required
- Consistency and consensus in plain words: linearizability, CAP, and one shared problem required
- Correctness in a distributed system in plain words: the end-to-end argument, exactly-once, integrity versus timeliness
- Distributed patterns: data consistency across services in Go
- Resilience Patterns: Retry, Circuit Breaker, Bulkhead, DLQ in Go
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 15. Kubernetes and graceful shutdown · 34 questions
Cluster, networking, Kubernetes deployment and operations, plus graceful service shutdown.
- Kubernetes: pod, deployment, service — where to start required
- Networking in Kubernetes: Service, DNS, Ingress, NetworkPolicy required
- Deploying to Kubernetes: manifests, Helm, rolling update, GitOps required
- Kubernetes in practice: debugging pods and kubectl commands
- OpenShift: How It Differs from Vanilla Kubernetes
- Helm
- Argo CD
- Go: server configuration and readiness during graceful shutdown
- HTTP drain in Go — how to correctly stop an HTTP server
- Database and persistence during graceful shutdown of a Go service
- Background goroutines and the outbox-relay during graceful shutdown in Go
- Kafka shutdown in Go: stopping the consumer and producer without losing messages
- Idempotency of in-flight operations in Go
- Kubernetes and graceful shutdown in Go: terminationGracePeriodSeconds, probes, rolling update
- Shutdown budgets and observability in Go
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 16. Clouds · 87 questions
Cloud principles and three providers — AWS, Azure and GCP: networking, IAM, compute, scaling, serverless, data, storage and IaC. One model, knowledge transfers between clouds.
- Что такое облако required
- Регионы и зоны required
- Учётные записи и права required
- Сеть required
- Вычисления required
- Управляемые данные required
- Наблюдаемость и секреты required
- Деньги required
- Отказоустойчивость required
- AWS Fundamentals: Accounts, IAM, Regions, and VPC required
- Networking in AWS: VPC, subnets, NAT and security groups required
- IAM in AWS: Users, Roles, and Policies required
- Where to run a service in AWS: EC2, ECS, EKS or Lambda required
- Scaling and Availability in AWS required
- Serverless on AWS: Lambda, events, cold start, API Gateway required
- Managed Data in AWS: RDS, ElastiCache, SQS, MSK required
- DynamoDB: keys, indexes, and when to pick it over SQL
- Security and observability in AWS: Secrets Manager, SSM, KMS, CloudWatch required
- AWS cost optimization: where to start
- Resilience and Disaster Recovery in AWS
- AWS Well-Architected Framework: six pillars and how to use them required
- Infrastructure as Code: the basics
- Terraform: HCL, Providers, State, and Modules
- CloudFormation: Templates and Stacks
- AWS CDK: infrastructure as a program
- IaC in Practice: State, Secrets, Delivery
- Основы
- Сеть
- Entra ID и RBAC
- Где запускать сервис
- Масштабирование и доступность
- Serverless
- Управляемые данные
- Cosmos DB
- Blob Storage
- Из Spring Boot
- Безопасность и наблюдаемость
- Оптимизация затрат
- Отказоустойчивость и DR
- Инфраструктура как код
- Основы
- Сеть
- Cloud IAM
- Где запускать сервис
- Масштабирование и доступность
- Serverless
- Управляемые данные
- Firestore и NoSQL
- Cloud Storage
- Из Spring Boot
- Безопасность и наблюдаемость
- Оптимизация затрат
- Отказоустойчивость и DR
- Terraform
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 17. CI/CD: the delivery pipeline · 19 questions
Pipeline principles, release strategies, branching and delivery.
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Phase 18. Quality: test strategy · 8 questions
The test pyramid, slices and integration tests, mocks and external services, load testing.
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Phase 19. Observability and diagnostics · 30 questions
How to see what a running system is doing: logs, metrics, tracing, context propagation, health checks, SLOs and alerts — plus database diagnostics and the incident review afterwards.
- Наблюдаемость
- Logging in Go: slog, JSON and context.Context
- Metrics in Go: prometheus/client_golang, RED, USE and business counters
- Distributed tracing in Go: OpenTelemetry from scratch
- Context propagation in Go — context.Context, middleware and goroutines
- Health checks in Go: liveness, readiness and /info
- SLO and alerts in Go: error budget and multi-window burn rate
- Observability configuration in Go: management port, logs and metrics
- Постмортем и дежурства required
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 20. Working with AI agents · 39 questions
How a language model works and how to write code productively with an AI agent: tokens and hallucinations, context, tool calling, agents, the working loop, reviewing and accepting AI code.
- How AI Models Work: Predicting the Next Token required
- AI Hallucinations: Why the Model Confidently Makes Things Up required
- Tokens and Cost: What You Pay For When Working With AI
- Context: What the Model Holds in Mind at Once required
- Tool Calling: How the Model Reaches Beyond Text required
- Agents: A Model in a Loop with Tools and a Goal required
- Working with Agents: The Basic Loop of a Productive Session required
- Команды Claude Code required
- Spec-driven development
- Reviewing and Testing Code with an Agent
- Accepting AI output: acceptance criteria and tests from the spec required
- AI as the product engineer's leverage required
- Configuring an agent for your project: rules, memory, tools required
- Which Programming Language to Choose for AI Coding
- Daily work with an agent: understand, build, fix required
- How to Review Code Written by AI required
- Executable agent rules vs SonarQube vs ESLint vs tech lead review
- Phase test in the cabinet
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Phase 21. Building LLM applications · 16 questions
How to embed AI into a backend product: what an LLM feature is made of, orchestration with LangChain, RAG and embeddings, vector databases, and agent applications.
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Phase 22. System design and architectural choices · 32 questions
The design method, building blocks and choices around storage, synchronicity and notations.
- Reliability, scalability, maintainability — in plain words required
- The system design method: from requirements to architecture required
- Building Blocks of System Design required
- How a Notification System Works: Architecture From Scratch
- How to write and defend a system design: design doc, C4, review required
- ADR: how to record architecture decisions required
- The Architect's Role in a Development Team required
- C4 model
- Mock interview in the cabinet
- Phase test in the cabinet
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Phase 23. Domain-Driven Design · 19 questions
Strategic and tactical patterns, integration and domain design principles.
- What DDD Is and Why You Need It required
- Strategic DDD Patterns in Go
- DDD Tactical Patterns in Go
- DDD Integration Patterns in Go
- Design Principles in DDD in Go
- Ontology and the domain model: a system of concepts before aggregates
- Event Storming: extracting the domain model from the business
- Phase test in the cabinet
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Phase 24. Service architecture patterns · 36 questions
Service structure, Onion and Hexagonal, CQRS, resilience and batch processing (in Go).
- Onion Architecture required
- CQRS
- When to apply CQRS in a Go service
- The command side in CQRS with Go
- The query side in CQRS with Go: how to read data properly
- Read-model in CQRS (Go): where to store it and how to update the projection
- Synchronizing the read-model via events in Go
- CQRS tier and evolution in Go
- Hexagonal architecture
- When to Use Hexagonal Architecture in a Go Service
- The Core Layer in Go: Hexagonal Architecture
- Ports in Hexagonal Architecture — How the Core Talks to the Outside World (Go)
- Inbound Adapters in Hexagonal Architecture with Go
- Out Adapters in Hexagonal Architecture in Go
- Hexagonal Architecture Package Structure in Go
- Bootstrap and Composition Root in Hexagonal Architecture (Go)
- Hexagonal Architecture Tests in Go
- Batch Data Processing: How Not to Break Your Background Worker in Go
- Event Sourcing: Store Events, Not State
- Phase test in the cabinet
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Phase 25. Development methodologies and process · 19 questions
Waterfall, Agile, Scrum, Kanban, XP, estimation and scaling — how a team organizes work from idea to release.
- Development Models: From Waterfall to Agile required
- Scrum: Roles, Events, and Artifacts required
- Kanban: Flow, WIP Limits, and Pull required
- Extreme Programming: the Engineering Practices of Agile
- Estimation and planning: story points and velocity
- Scaling Agile: SAFe and LeSS
- A Methodology for AI: Use Case Pattern and Other Ways
- Phase test in the cabinet
Программа обучения v11.1.69
Backend · Go
A Go backend training program: sixteen phases from the Go stack (net/http, chi, sqlc+pgx) through data, design principles and patterns, search, infrastructure, and quality to system design and DDD, culminating in the Use Case Pattern, and finally an end-to-end marketplace case study. The conceptual phases are shared across languages; the tooling ones are Go-specific.
The program has 863 self-check questions in total.