AWS Partner Network (APN) Blog

We’re excited to bring you AWS re:Invent 2026 both in-person and virtually! The conference is November 30 – December 4 in Las Vegas, with virtual opportunities to watch keynotes and Innovation Talks live. To help you prepare, we curated a list of key re:Invent information for AWS Partner and AWS Marketplace communities.

As agent estates grow from a handful of pilots to hundreds of agents in production, teams need to decide which agents to stop and which to promote. This post shows how Dataiku Agent Management works with Amazon Bedrock AgentCore and Amazon CloudWatch to discover, monitor, and control agents, using the signals AgentCore already emits.

As AWS Outposts deployments scale across multiple teams and customers, platform teams must share a finite pool of compute and storage without turning each request into a manual ticket. This post explores how a cloud management platform can turn a shared Outpost into governed, self-service cloud infrastructure. It covers tenant lifecycle, self-service provisioning, per-tenant capacity and quota management, role-based access, and consolidated billing across your Outpost and the parent AWS Region. It shows how CloudPrimus helps allocate capacity to each account that needs it, while preserving governance and auditability. This helps provide a consistent multi-account operating model that complements native AWS capabilities.

Learn how Kaufman Rossin partnered with Fisent Technologies, Launchpad.io by Pegasystems, and AWS to transform manual Regulation E compliance testing into a scalable Outcomes-as-a-Service solution. The service combines deterministic workflow automation, applied generative AI, and cloud-native AWS infrastructure. It has processed more than 100,000 dispute cases across 30+ fintechs. Along the way, Kaufman Rossin achieved 70% faster testing and 50% fewer manual hours.

AI agents are making mainframe modernization programmable. This post walks through a data-first migration pattern that pairs Qlik Replicate’s log-based Change Data Capture (CDC) with the agentic AI of AWS Transform and Kiro. Using the strangler fig pattern and blue/green deployment, it migrates wave by wave, keeping the mainframe as system of record until each module is validated and the mainframe is finally decommissioned. Rising hardware costs, a shrinking COBOL and PL/I talent pool, batch-processing limits, and constrained innovation are driving organizations to make the move.

Demand forecasting works at catalog scale, but value still leaks in the last mile, where a forecast must become a placed order. This post describes a pattern that closes that gap: Databricks Many Model Forecasting and a Genie Agent surface the forecast, and Amazon Quick reconciles it against an external supplier feed, placing routine orders automatically and escalating only the exceptions. The pattern applies well beyond supply chain.

Managing AI costs is a top challenge for organizations scaling generative AI on AWS. This post shows how AWS CUR 2.0, Amazon S3, and AWS Trusted Advisor form the data foundation that New Relic Cloud Cost Intelligence builds on for Amazon Bedrock workloads. The result is token-level cost visibility inside the observability workflows engineering teams already use, shifting AI from opaque experimentation to disciplined, ROI-driven operations.

AI growth in regulated environments put pressure on the systems that govern your data. You need to give teams timely access to approved datasets without losing control of data placement, lineage, or reproducibility. In this post, we share three data architecture principles, show how Domino Data Lab applies them with Amazon FSx for NetApp ONTAP, and give you workload-level metrics to evaluate the architecture.

Banking, financial services, and insurance (BFSI) institutions need AI systems that can act autonomously at market speed, but autonomy without governance is a nonstarter in an industry defined by regulatory intensity and operational risk. In this post, Apexon and AWS present an architecture-first approach to operationalizing agentic AI on AWS, with governance built in from the start across three layers: intelligence, orchestration and execution, and governance, security, and audit. Learn how governed agentic patterns apply to core BFSI workflows like customer onboarding, credit processing, and payments exception handling, enabling autonomy at scale while keeping every action traceable and auditable.

We are excited to highlight 137 AWS Partners that received new or renewed specializations in October for our global AWS Competency and AWS Managed Service Provider (MSP) programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.

AI agents authenticate, hold permissions, and act on data, yet most organizations manage them as application components rather than governed identities. Learn how Saviynt Zuma works with Amazon Bedrock AgentCore to govern agents as first-class identities, from registration and least-privilege provisioning through runtime authorization, certification, and deprovisioning. Security teams can then answer which agents exist, who owns them, and what they can access.