Today, AI services rely heavily on API keys. To run AI agents, users provide API keys that signify paid tokens, subscriptions, or paid accounts. While API keys are easy to use, it is just as easy to use them unsafely. The result of a hijacked key is a compromised environment that is misused or abused […]
API Keys Are Open Secrets Read More »
When your application calls an AWS service and the request fails with a retryable error, the AWS SDK retries it automatically. The retry behavior controls how long the SDK waits between attempts and when it gives up. Most of this happens in the background, but it directly affects how your application experiences errors and latency.
Announcing updated retry behavior for AWS SDKs and Tools Read More »
Cyber resilience is the ability to recover workloads to a known-good state after an adversary has affected the environment. Prevention works to keep threat actors out and detection works to find them quickly. Cyber resilience focuses on recovery: restoring a trustworthy environment when backups, credentials, or parts of the infrastructure can no longer be assumed
LLMs have become more powerful at smaller sizes, but deploying them to edge devices like smartphones remains a massive challenge. Today, developers have to optimize across a sprawling combination of accelerators, operating systems, and countless System-on-a-Chip (SoC) configurations, often relying on manual testing with just a handful of devices. Google AI Edge Portal helps solve
Benchmark and optimize LLMs on-device with AI Edge Portal Read More »
Editor’s note: Urban Outfitters, Inc. (URBN) recently completed a major infrastructure upgrade, migrating its IBM Sterling Order Management System (Sterling OMS) from an Oracle database to Google Cloud’s AlloyDB for PostgreSQL. This strategic move, a testament to the growing partnership between Google Cloud and IBM, delivers significant benefits for URBN, paving the way for increased
As models and harnesses improve, agents are taking on increasingly complex tasks that can run for hours or even days. But as we push agents to do more, this has surfaced a new operational problem: long-running agent workflows are fragile and incredibly hard to manage reliably and efficiently in production. Today, we’re introducing Agent Executor,
Introducing Agent Executor, Google’s distributed Agent Runtime Read More »
LLMs have become more powerful at smaller sizes, but deploying them to edge devices like smartphones remains a massive challenge. Today, developers have to optimize across a sprawling combination of accelerators, operating systems, and countless System-on-a-Chip (SoC) configurations, often relying on manual testing with just a handful of devices. Google AI Edge Portal helps solve
Benchmark and optimize LLMs on-device with AI Edge Portal Read More »
In just a short time, we’ve seen AI transition from simple chat interfaces to autonomous agents capable of function calling, code execution, and persistent terminal use. But to orchestrate these capabilities securely, agents need more than just intelligence — they need a robust, hyper-scalable, secure compute environment in which to execute code. Since our preview
Agent Sandbox on GKE is now available for everyone, and a first look at Agent Substrate Read More »
Ryan welcomes Jaime DeLanghe, chief product officer at Slack, to chat about how they’re preparing to integrate everybody’s agents in their chat application.
Pack your agentic stack in Slack Read More »
This is a new era — the agentic era – and the question is no longer, “what’s possible?” but rather, “what creates impact?” Today, organizations across industries around the world are swiftly moving from AI exploration and pilots to real-world use cases that drive impact, at scale. They are doing this with agents. In order
The agentic era: Architecting the blueprint for mission impact across the public sector Read More »
