OffNet Newsroom

Daily topic roundup

AWS

Tuesday, July 28, 2026 · 8 stories, curated & summarized — click any story for the source.

Amazon RDS for SQL Server now allows restoring Transparent Data Encryption-enabled databases on Multi-AZ instances and same-region read replicas. Previously, this operation was restricted to Single-AZ configurations, forcing users to disable TDE or migrate. The process requires backing up the TDE certificate to Amazon S3 and restoring it to the target instance before performing the database restore.

  • Eliminates the need to disable TDE or switch to Single-AZ for encrypted database restores
  • Supports restore operations on Multi-AZ instances and same-region read replicas
  • Requires pre-storing the TDE certificate in Amazon S3 for restoration
  • Maintains encryption posture during disaster recovery and replication scenarios

Fleet impact: Enables seamless encrypted restores for SQL Server workloads on RDS Multi-AZ and read replicas, removing the operational friction of disabling TDE or migrating to Single-AZ. Ensure TDE certificates are securely stored in S3 and accessible to the target RDS instance to avoid restore failures.

HOW IT WORKSRestoring TDE Encrypted Databases1Backup TDE Certificate to S32Restore Certificate to Target Instance3Restore Database on Multi-AZ or Replica

AWS has launched a public preview of the GuardDuty Investigation Agent, designed to automate threat analysis by correlating findings with 90-day activity logs and resource topologies. The agent generates structured reports featuring risk ratings, confidence scores, and MITRE ATT&CK classifications. These capabilities are accessible via the AWS MCP Server, enabling integration with agentic tooling for automated workflows.

  • Agent correlates GuardDuty findings with historical logs and topology data for richer context.
  • Reports include structured risk ratings, confidence scores, and MITRE ATT&CK mappings.
  • Integration via AWS MCP Server allows agentic tooling to trigger and manage investigations.
  • Public preview is limited to 10 investigations per account per day.

Amazon Neptune now allows administrators to use AWS resource tags and IAM principal tags as conditions in IAM policies and Service Control Policies. This tag-based access control eliminates the need to enumerate specific cluster ARNs when governing access to Neptune data-plane operations. The feature supports dynamic, attribute-based enforcement of organizational access boundaries for customers managing multiple clusters at scale.

  • Enable dynamic access control by matching IAM principal tags to Neptune cluster tags in policies.
  • Simplify policy management for large fleets by avoiding static ARN enumeration in IAM rules.
  • Scope Neptune-db:* actions to specific clusters using tag conditions in IAM or SCPs.
  • Leverages existing VPC, TLS, and IAM authentication layers for comprehensive security.
TRADE-OFFNeptune Access Control EvolutionLegacy MethodEnumerate specific cluster ARNsStatic policy managementHard to scaleTag-Based MethodUse IAM and resource tagsDynamic attribute-based enforcementSimplified for large fleetsvs

AWS has removed the mandatory Self-Managed License (SML) prerequisite for creating Host Resource Groups (HRGs) on EC2 Dedicated Hosts. This change simplifies setup for customers seeking hardware isolation or running EC2 Mac instances, eliminating the need for AWS License Manager configuration. BYOL workloads can still use SMLs for strict AMI restriction and license tracking if desired.

  • HRGs can now be created without Self-Managed Licenses, reducing configuration overhead.
  • Ideal for hardware isolation needs or EC2 Mac instances where BYOL is not applicable.
  • BYOL customers retain the option to use SMLs for AMI restriction and license tracking.
  • Disable the 'Restrict to AMIs' option or use license-conf to bypass SML requirements.
CHECKLISTSimplified HRG Setup GuideCreate HRGs without Self-Managed LicensesIdeal for hardware isolation needsSupports EC2 Mac instancesRetain SML for BYOL tracking

Uber has implemented a Zero Growth Stack strategy that separates infrastructure capacity expansion from business demand fluctuations, thereby reducing hardware requirements while maintaining service scalability. The approach relies heavily on optimizing garbage collection to improve efficiency. Simultaneously, the company integrates generative AI into the development workflow to boost productivity, paired with strict cost controls to ensure economic viability.

  • Decouple infrastructure scaling from business demand to minimize hardware waste.
  • Optimize garbage collection as a core lefthand-side performance driver.
  • Adopt GenAI for dev productivity but enforce strict cost governance.
  • Balance AI integration with economic efficiency measures to prevent budget overruns.

Amazon EKS now allows teams to revert their cluster's control plane to the previous Kubernetes version within seven days of an upgrade. This feature acts as a safety net to mitigate risks associated with in-place cluster updates. It enables faster recovery when a new version introduces compatibility issues or instability.

  • Rollback window is strictly limited to 7 days post-upgrade.
  • Applies specifically to the cluster control plane version.
  • Reduces risk of in-place upgrades by providing a quick recovery path.
  • Enables immediate remediation for problematic Kubernetes version updates.

The technology industry has undertaken a historic infrastructure expansion totaling $1 trillion to support AI workloads. Analysts report that this massive capital expenditure is driving up prices for both hardware and software components. Ultimately, these increased production and infrastructure costs are being transferred to end customers.

  • AI infrastructure build-out has reached $1T, the largest in history
  • Hardware and software prices are rising due to supply constraints
  • Cost increases are being passed directly to customers via bills
  • Analysts link spending surge to broader market price inflation

Amazon Kinesis Data Streams extends its On-demand Advantage mode to allow proactive scaling down of ingest capacity via warm throughput. Users can set a lower warm throughput value to reduce write throughput, though the stream ensures it maintains at least the capacity required for peak ingest over the last hour. This feature provides full control over both up and down scaling of stream write throughput.

  • Warm throughput now supports scaling down, not just up, for On-demand Advantage mode.
  • Set a lower warm throughput value to proactively reduce stream write capacity.
  • Stream retains capacity needed for peak ingest in the last hour as a safety floor.
  • Enables granular control over Kinesis stream costs and performance during traffic drops.
CHECKLISTScale Down Kinesis IngestEnable On-demand Advantage modeSet lower warm throughput valueProactively reduce write capacityMaintain peak ingest safety floorControl costs during traffic drops