Observability stories
Enterprises could cut software release delays as the partners add self-healing AI agents to automate testing across existing systems.
IT teams can now reuse resolved support tickets as scripts, aiming to cut repeat incidents across managed devices and speed fixes.
Enterprise teams can now impose one policy layer across Zapier workflows, agents and SDK-built apps as AI use outpaces governance.
SREs can now keep PromQL workflows intact as Elastic Observability brings metrics, logs and traces into one environment.
Pressure is mounting on platform teams to prove AI can cut outage risk and costs without adding fresh complexity to production systems.
Enterprises could query lakehouse data without moving it, as the database firm adds managed deployment, Arm processors and AI tools on Google Cloud.
Engineering teams can now keep decisions, fixes and costs in one place as CodeRabbit brings its AI agent into Slack.
Broadcasters can now cut latency and costs during major live events as Google expands regional capacity and adds new monitoring tools.
Businesses are turning to observability software to govern AI traffic and secure hybrid systems, as IDC sees the market rising to USD $4.39 billion by 2029.
Rising AI infrastructure bills are pushing teams to hunt for idle chips and bottlenecks, as GPUs account for 14 per cent of compute costs.
Enterprises get tighter controls for autonomous AI agents and Cloud SQL backups as Rubrik expands its Google Cloud security stack.
Its new fabric promises lower latency and more bandwidth for training, as Google links up to 134,000 TPU 8t chips across sites.
Nearly half of organisations now treat mixed on-premise and cloud estates as permanent, with security and cost pressures mounting.
The new tools could let firms’ AI agents act on live data more securely across clouds, while cutting rebooking from hours to minutes.
Users of Loki should see far quicker searches for rare log values, after Logline’s indexing tech cut one UUID scan from 3.5 TB to 8 GB.
The release aims to ease log searching and dashboard management as engineering teams wrestle with rising telemetry volumes and system complexity.
Businesses can now let Gemini agents run for hours or days, while new controls aim to keep AI workflows traceable and secure.
Adoption of AI agents in business is creating a new infrastructure bottleneck as companies struggle to coordinate systems across clouds and partners.
Existing deployments can gain stronger protection against post-compromise persistence without changing Dockerfiles, CI/CD pipelines or runtime workflows.
Native checks will now flag prompt injection and data leakage across more of the AI agent stack as enterprises push systems into production.