Habr•September 4, 2026•🇷🇺Translated from Russian

OTUS Publishes September Digest of Free Lessons on Linux Administration, PostgreSQL, CI/CD and Infrastructure Security

OTUS has published its September digest of free lessons for engineers responsible for infrastructure, covering Linux, databases, CI/CD and security topics.

The company offers practicing specialists an opportunity to attend online sessions led by current instructors who demonstrate technologies on real production cases.

Administration of Linux and servers

  • 7 September 20:00 – Linux for Windows administrators in 60 minutes
  • 17 September 20:00 – Where Linux stores settings and logs: practical analysis of the file system structure
  • 21 September 20:00 – Typical tasks with RAID arrays: creation, operation, data migration and recovery
  • 22 September 20:00 – Top GPO policies that will help you
  • 24 September 19:00 – Can AI fix a Linux server: where hints end and engineering diagnostics begin

Performance, databases and high availability

  • 8 September 20:00 – Fighting locks in PostgreSQL: achieving high concurrency under heavy load
  • 8 September 20:00 – LVM without downtime: volume expansion, data migration and emergency rollback via snapshot
  • 23 September 20:00 – Using Patroni to manage highly available PostgreSQL clusters
  • 23 September 20:00 – eBPF: X-ray vision for production

Infrastructure automation and DevOps

  • 10 September 20:00 – Setting up GitLab Runners
  • 17 September 20:00 – Release management in 1C: GitFlow, code review and CI/CD in practice (pre-recorded webinar)
  • 9 September 20:00 – Go profiling: how to find and fix bottlenecks in production

Infrastructure security

  • 22 September 20:00 – Automating traffic management with mitmproxy
  • 22 September 20:00 – Can AI-generated code be trusted: finding hallucinations, vulnerabilities and outdated solutions

AI in the work of an engineer

  • 8 September 20:00 – AI versus bugs: how to analyze an incident in a Python project from logs to fix
  • 21 September 20:00 – One working day with AI: from emails and tables to a ready presentation for management

Related topics for engineer growth

  • 8 September 20:00 – From technical leader to CTO: how to start making business-level decisions
  • 9 September 20:00 – How a team lead can distribute responsibility without becoming a bottleneck

Related articles

Habr•Other

Yandex Black October: How Architectural Flaws and Capacity Mismanagement Turned Data Center Losses Into a 11-Day Fintech Coma

In October 2026 three Yandex data centers in Central Russia were physically destroyed within days, triggering the collapse of Yandex Cloud and multiple core services. Between the first and third site failures engineers had 74 hours to restore quorum and rebalance workloads yet failed to do so because Control Plane components remained tied to the lost zone and spare capacity had been eliminated to cut costs. Core banking and BNPL systems entered Read-Only mode after losing quorum, forcing a complete stop-the-world reconciliation that lasted until 22 October. Backups stored inside the same regional S3 buckets proved unusable, resulting in a seven-day RPO and primary-key collisions after restoration. The incident exposed that Metro-Cluster designs had been incorrectly treated as full Disaster Recovery and that aggressive AP microservice patterns created logical split-brain conditions outside the database layer.

AntiMalware•Other

Astra Group Releases Low-Code Astra AI Platform for Building Corporate AI Agents in Closed Environments

Astra Group has launched the Astra AI Platform, a low-code constructor designed for creating corporate AI applications that operate entirely within closed circuits without reliance on foreign clouds. The platform targets small and medium businesses as well as large corporations, enabling rapid deployment of AI secretaries, technical support assistants, and other agents in days rather than months. It forms part of the broader Astra AI ecosystem and includes two main constructors: one for machine learning model training and deployment, and another for LLM-based language assistants, document search, and process automation. Users can assemble scenarios from visual blocks, debug them in real time, or extend functionality with custom Python code when needed. The solution supports RAG-based knowledge bases, integration with external tools such as CRM and ERP systems, and the coordination of multiple agents for distributed task handling. One demonstrated use case involves processing ten pages of engineering drawings and specifications in five minutes to prepare data for downstream systems. The product is already listed in the Russian domestic software registry and available to customers.

Habr•Other

Multi-Tenancy Isolation in VictoriaMetrics, VictoriaLogs and Grafana: Building Client Separation in a Shared Stack

Voltir runs a single shared monitoring stack consisting of VictoriaMetrics, VictoriaLogs, Grafana and vmalert for all customers instead of deploying separate instances per tenant. Isolation relies on numeric account IDs enforced at every layer: nginx validates tokens against the platform API before proxying writes, Grafana data sources hard-code tenant accounts, and vmalert rules receive automatic account filters. The team discovered that a single malformed rule or template could break alerting for every tenant because vmalert loads the entire rules directory at once. They also found that Grafana automatically created personal organizations granting Org Admin rights, accumulating hundreds of orphaned organizations and users that consumed disk space and resources. A dedicated cleanup module plus hourly reconciliation now removes rules, organizations, series and users when a tenant is deleted, while isolation tests verify both data and API objects across tenants.

AntiMalware•Other

The Real Costs of Using Claude and GPT for Russian Businesses Exposed

Accessing generative AI models like Claude and GPT has become straightforward for Russian companies, yet calculating their true expenses remains complex. Hidden factors such as intermediary commissions, currency conversion rates, taxes, and the often-overlooked costs of model reasoning tokens can double or triple initial estimates. Founder Vitaly Nagay of the Heli service analyzed these financial and organizational risks for Russian firms relying on foreign AI providers. In one example, a support department processing 20,000 monthly queries sees costs rise from $240 to $480 when reasoning tokens are included. Nagay recommends evaluating providers by dividing actual ruble charges by the model's official dollar pricing to reveal hidden markups. Additional concerns involve data control, document compliance, and access history when employees use personal subscriptions. Companies are advised to verify billing details, data storage policies, and issue dedicated API keys with spending limits before procurement.