PSLC and Agent-Ops: From Product Support to Infrastructure Transformation
Sergey Zhitinsky, founder of Git in Sky, shared insights from the OPS Talk by Sber meetup held on 19 October, where he examined the PSLC methodology presented by architect Alexander Shapovalov.
PSLC (Product Service Lifecycle) addresses the full service journey by combining immediate incident response with long-term improvements to processes, knowledge, and product design. It features two interconnected loops: one for service execution and another focused on building reliability and trust.
In contrast, Agent-Ops provides a granular eight-step framework for handling specific infrastructure tasks. These steps include defining intent, gathering evidence, performing diagnostics, creating a plan, obtaining approval, executing a controlled change, verifying outcomes, and extracting lessons. The methodology explicitly separates planning, human decision-making, and execution.
The article demonstrates their combined application through a realistic incident: after a release, increased logging fills the database disk, slowing order processing in an online store. PSLC manages the overall service recovery and subsequent reliability work, while Agent-Ops guides the infrastructure change such as expanding storage or safely removing old logs.
Both methodologies stress the importance of documented knowledge, controlled actions, and clear human responsibility. Agent-Ops v0.5.1 requires human approval and manual triggering of changes even in production, distinguishing it from fully autonomous execution models.
Resource considerations differ: PSLC benefits from centralized platforms and expertise pools typical in large organizations like Sber, whereas Agent-Ops aims to support compact teams that may lack such infrastructure.
Related articles
Building Your First Home Network Lab: Essential Tools and Experiments to Understand Corporate Networks
A cybersecurity professional without network knowledge resembles a guard without a building blueprint, spotting alarms but unable to trace the intruder. Setting up a personal lab on a standard computer bridges this gap through virtualization and hands-on practice with protocols and attacks. The guide recommends GNS3 for topology emulation, VirtualBox or VMware for running Windows and Linux workstations, Cisco Packet Tracer for quick simulations, Wireshark for traffic analysis, and draw.io for diagramming. Key experiments include configuring Cisco IOS routers with IP addressing, testing default gateways, observing ARP requests and replies, triggering broadcast storms via switch loops, and enabling STP to prevent loops. The lab demonstrates how legacy protocols like ARP expose networks to spoofing and why segmentation with VLANs and firewalls matters. Resources from CyberED provide demo access to courses on SOC analysis, penetration testing, and AI applications in security to extend learning.
Russian Organizations Allocate 4.5 Trillion Rubles to Innovation Spending in 2025
Large and medium-sized Russian organizations directed a total of 4.5 trillion rubles toward innovation activities during 2025. Nearly half of the expenditure originated from the services sector, while information technology and telecommunications accounted for 860.9 billion rubles. The Institute for Statistical Studies and Economics of Knowledge at HSE University published the figures based on Rosstat data, showing an innovation intensity rate of 2.7 percent. Services companies alone contributed approximately 2.3 trillion rubles, including 882.7 billion rubles for research and development. Astra Group IR Director Vladislav Anshakov outlined major spending areas such as product development, cloud and AI hardware, and acquisitions of technologies and teams. The group expanded its portfolio with the Perseus DBMS and a 26 percent stake in AI developer AIB. More than one-third of organizations cited high costs and insufficient internal funds as key barriers to further innovation.
Telegram macOS Developer Says 99.9% of Client Code Is Now Written by AI and Suggests Firing Manual Coders
Mike, the developer of the official Telegram client for macOS, stated that artificial intelligence now generates 99.9 percent of the messenger's client code. He argued that programmers who continue writing code manually should be dismissed. In a Telegram discussion, Mike cited the gram.org website as an example created entirely with AI assistance in a single day, with domain support from Pavel Durov. He also described adapting the iOS client for a foldable iPhone Duo overnight using Claude. According to Mike, even designers are now contributing to client code, and 80 to 90 percent of Telegram developers share his positive view of AI tools. When participants raised questions about code quality and security, Mike replied that AI also identifies and fixes vulnerabilities, claiming the resulting code is superior to human-written equivalents. He further announced plans to open a new GitHub repository for the macOS client source code, as the previous repository had not been updated for over a year.
Secure Boot on Arch Linux: Enabling Protection for UKI Without Replacing Factory Keys
A detailed guide explains how to configure Secure Boot on Arch Linux for Unified Kernel Images without replacing the motherboard's factory keys or relying on Microsoft certificates. The author chose the minimal-intervention approach of adding a custom key to the existing DB section via the UEFI interface instead of using sbctl enroll-keys or shim. The process begins with backing up existing keys to a FAT-formatted USB drive directly from the BIOS menu. New keys are then generated using sbsigntools and openssl, converted to DER format, and enrolled through the ASUS Prime 790-P UEFI interface. A post-hook script for mkinitcpio automatically signs the UKI after every kernel update, ensuring the entire unified image remains protected. The method preserves the original Microsoft and vendor certificates while adding only the user's own signing key.