# KMS Published articles for KMS. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## New in Symfony 8.2: KeyManagement Component DevFeed: [New in Symfony 8.2: KeyManagement Component]() Original publisher: [Read original article]() Author: Javier Eguiluz Published: 2026-09-15T07:11:00Z Content type: release Language: en Sources: [Symfony Blog]() Topics: [Symfony](), [Encryption](), [Amazon Web Services](), [Azure](), [Google]() Tags: [2026](), [api](), [article](), [aws](), [azure](), [backend](), [encryption](), [features](), [google](), [hashicorp-vault](), [kms](), [new-features](), [openssl](), [sdk](), [symfony]() ### AI overview Symfony 8.2 introduces an experimental KeyManagement component that provides one API for AWS KMS, Azure Key Vault, Google Cloud KMS, and HashiCorp Vault. It supports direct and envelope encryption, local development backends, provider bridges, console commands, debug-toolbar integration, and Doctrine support. ### Source excerpt This is the first article in a series showcasing the most important new features introduced by Symfony 8.2, which will be released at the end of November 2026. Contributed... ## Migrate CloudFormation to Pulumi with Discovered Stacks DevFeed: [Migrate CloudFormation to Pulumi with Discovered Stacks]() Original publisher: [Read original article]() Author: Alejandro Cotroneo Published: 2026-07-30T00:00:00Z Content type: tutorial Language: en Sources: [Pulumi]() Topics: [Infrastructure as code](), [AWS CloudFormation](), [migration](), [Amazon Web Services](), [VPC](), [Amazon S3](), [DynamoDB](), [AWS IAM]() Tags: [aws](), [cloudformation](), [dynamodb](), [git](), [iac](), [iam](), [import](), [insights](), [kms](), [migration](), [pulumi](), [pulumi-cloud](), [pulumi-neo](), [s3](), [tutorials](), [vpc]() ### AI overview A tutorial shows how to migrate a 61-resource AWS CloudFormation stack to Pulumi using Discovered Stacks in Pulumi Cloud. It explains how to find the stack, review migration status, start the migration, resolve unmatched resources, and verify the result with a zero-diff pulumi preview. ### Source excerpt With Discovered Stacks, Pulumi Cloud does the bookkeeping for a CloudFormation migration: every resource in the stack gets an explicit migration status, and the migration is done when the code provably matches the cloud. In this tutorial, we take one real CloudFormation stack from discovered to migrated and managed by Pulumi IaC, end to end. What we're migrating Our example is payments-api, a CloudFormation stack with 61 resources: a VPC, an Aurora ledger database behind an RDS Proxy, an assets S3 bucket, a DynamoDB ledger table, a Kinesis payment-events pipeline, and the IAM roles, KMS keys, and secrets that wire them together. The plan has five steps: Find the stack in Pulumi Cloud. Review the migration breakdown at a glance. Start the migration. Resolve the stragglers, so every resource is accounted for. Confirm the quality gate: a zero-diff pulumi preview. We'll use Pulumi Neo to do the heavy lifting, but nothing here depends on it. The same flow works with your own coding agent or entirely by hand, because migration status is derived from actual stack state -- however the work gets done, the console shows the same progress. Step 1: Find your stack in Pulumi Cloud Discovered Stacks builds on Discovery, so the only prerequisite is a scanned cloud account -- the AWS account holding your CloudFormation stacks. Once a scan has run, open the Stacks page and turn on Show Discovered Stacks. Your CloudFormation stacks appear alongside your Pulumi stacks. The project name comes from the CloudFormation stack (payments-api), and the stack name encodes the account and region it came from, so the same template deployed to two regions shows up as two distinct discovered stacks. Step 2: Plan the migration at a glance Open the discovered stack's Migration tab. It lays out all 61 resources of payments-api by status, so you can visualize the migration before touching anything: 54 Ready: mapped to a Pulumi type and confirmed to exist -- importable right now. 2 Not found: mapped, but ## Announcing Apache Iceberg 1.11.0 DevFeed: [Announcing Apache Iceberg 1.11.0]() Original publisher: [Read original article]() Author: Google Open Source (noreply@blogger.com) Published: 2026-05-27T18:30:00Z Content type: release Language: en Sources: [Google Open Source Blog]() Topics: [Apache Iceberg](), [Apache Spark](), [apache-flink](), [schema-evolution](), [Streaming](), [Encryption](), [Cryptography]() Tags: [apache-flink](), [apache-iceberg](), [apache-spark](), [encryption](), [kms](), [lakehouse](), [releases](), [schema-evolution](), [streaming]() ### AI overview Apache Iceberg 1.11.0 adds support for Apache Spark 4.1 and Apache Flink 2.1, makes both default build targets, and introduces changes including server-side REST catalog scan planning, partition statistics APIs, built-in envelope encryption with Google KMS support, and Google Storage Analytics integration. ### Source excerpt by Alex Stephen & Talat Uyarer, Lakehouse Apache Iceberg project has just launched version 1.11.0! A lot has happened since the last version. Iceberg 1.11.0 adds support for Apache Spark 4.1 and Apache Flink 2.1, the latest releases of the two engines and makes both the default build targets The rest are more structural. The REST catalog learns to plan scans server-side, shifting metadata work off the query engine. A new partition statistics scan API gives optimizers a clean, supported way to read a table's shape. Built-in table encryption arrives with envelope encryption and Google KMS support. And Google Storage Analytics library integration makes your Iceberg workloads faster than before. Let's take a look at some of the biggest changes. Spark & Flink Updates As Spark and Flink are moving forward, the 1.11.0 release is pushing forward for new version support in both. Spark 4.1 & DSv2 Migration: Spark 4.1 unlocks is MERGE INTO with automatic schema evolution: Spark's newer MERGE syntax accepts a WITH SCHEMA EVOLUTION clause, so a MERGE whose source carries columns the target table lacks can add those columns to the table within the same statement, with no separate ALTER TABLE round trip. Beyond the version bump, the 1.11 Spark connector also modernizes against Spark's newer DataSource V2 APIs and adds an asynchronous micro-batch planner that speeds up Structured Streaming. Flink Ecosystem Updates: Initial work for Flink 2.1 support has landed in the core repository, continuing Iceberg's promise of providing first-class, low-latency streaming sink capabilities. The centerpiece of the Flink work is the DynamicIcebergSink, an experimental sink that breaks the old one-sink-per-table model: a single sink routes each record to a table chosen at runtime, creating tables on demand and evolving their schemas and partition specs on the fly as the input changes including dropping columns once you opt in with dropUnusedColumns. In addition to DynamicIcebergSInk work Flink sta ## Encryption using data-specific keys DevFeed: [Encryption using data-specific keys]() Original publisher: [Read original article]() Author: Yoav Amit Published: 2024-12-12T00:00:00Z Content type: article Language: en Sources: [Cash App Code Blog]() Topics: [Encryption](), [Cryptography](), [Security](), [Architecture & Design](), [Scalability](), [Back end](), [Amazon Web Services](), [gRPC](), [Kafka]() Tags: [access-control](), [backend](), [cloud](), [decoupling](), [encryption](), [git](), [kafka](), [kms](), [scalability](), [security](), [server-security-encryption]() ### AI overview Cash App describes its evolution from service-centric application-layer encryption to a data-centric model called "Data Keys," which associates encryption keys directly with the data they protect. The change was made to improve flexibility and scalability as encryption expanded across services, gRPC transport infrastructure, and Kafka. ### Source excerpt Associating encryption keys with the data they protect ## Space secrets security update DevFeed: [Space secrets security update]() Original publisher: [Read original article]() Author: system Published: 2024-05-31T00:00:00Z Content type: news Language: en Sources: [Hugging Face - Blog]() Topics: [Security](), [incident](), [Authorization](), [spaces](), [tenant data protection]() Tags: [audit](), [authorization](), [data-protection](), [incident](), [infrastructure](), [kms](), [secrets](), [security](), [space](), [tokens]() ### AI overview Hugging Face reports unauthorized access involving secrets on its Spaces platform and suspects that some Spaces secrets may have been accessed. It revoked a number of HF tokens, recommended refreshing keys and tokens, and encouraged users to use fine-grained access tokens. The company also described security improvements including removing organization tokens, adding KMS for Spaces secrets, strengthening leaked-token detection and invalidation, and planning to deprecate classic read and write tokens. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## File encryption in Python: An in-depth exploration of symmetric and asymmetric techniques DevFeed: [File encryption in Python: An in-depth exploration of symmetric and asymmetric techniques]() Original publisher: [Read original article]() Author: Keshav Malik Published: 2023-11-22T05:00:00Z Content type: tutorial Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Encryption](), [Python](), [Cryptography](), [Amazon Web Services](), [SDKs](), [Command-line interface]() Tags: [amazon-web-services](), [application-security](), [awareness](), [blog](), [contentlab](), [cryptography](), [developer](), [encryption](), [engineering](), [kms](), [python](), [security](), [techniques](), [tutorial]() ### AI overview This tutorial explains symmetric and asymmetric file encryption in Python. It covers symmetric encryption with Amazon KMS and PyNaCl SecretBox, then introduces asymmetric encryption with PyNaCl's public/private box, including the prerequisites and packages needed to follow along. ### Source excerpt This article dives into the world of encryption in Python. For symmetric encryption, we'll focus on Amazon's Key Management Service (KMS) and PyNaCl SecretBox. Then, we'll look at asymmetric encryption and PyNaCl's public/private box. ## Serverless v1.15 - CLI autocomplete & Cognito User Pool trigger events added DevFeed: [Serverless v1.15 - CLI autocomplete & Cognito User Pool trigger events added]() Original publisher: [Read original article]() Author: Philipp Müns Published: 2017-06-09T00:00:00Z Content type: release Language: en Sources: [Serverless Blog]() Topics: [serverless framework](), [Serverless](), [Framework]() Tags: [autocomplete](), [aws](), [aws-lambda](), [cli](), [cloud-computing](), [event](), [events](), [faas](), [framework](), [function-as-a-service](), [infrastructure-as-code](), [kms](), [news](), [release](), [serverless](), [serverless-architecture](), [serverless-framework](), [v1]() ### AI overview The Serverless Framework v1.15 release adds CLI autocomplete, a Cognito User Pool Trigger event source, and KMS Key support. ### Source excerpt CLI autocomplete, Cognito User Pool Trigger event source, KMS Key support and more in the Serverless Framework v1.15 release.