Release notes, new features, deprecations, and announcements from Salesforce and AWS.
68
Total
20
Salesforce
45
AWS
32 notices (Announcement)
Article #99 covers the Kinesis family (Data Streams, Firehose, Data Analytics), shards, partition keys, Lambda consumers with parallelization_factor, Firehose zero-code delivery, enhanced fan-out, batch ingestion, and 6 common mistakes.
Article #98 covers RDS vs Aurora architecture, instance sizing (Graviton r7g), gp3 vs io2 storage, Multi-AZ failover, Aurora Serverless v2, RDS Proxy for Lambda, Performance Insights, and 6 common production mistakes.
Article #97 covers stream view types, Lambda consumers with partial batch failures, idempotent processing, fan-out via SNS, cross-region replication, OpenSearch indexing, and DynamoDB Streams vs Kinesis comparison.
Article #96 covers Serverless vs node-based, Graviton instances, cluster mode, Lambda connection patterns, TTL jitter, distributed locking, rate limiting, and 6 common ElastiCache production mistakes.
Article #95 covers User Pools vs Identity Pools, OAuth flows, JWT tokens (ID/Access/Refresh), federated login (Google, SAML), Lambda triggers for custom claims and DB sync, groups and RBAC, API Gateway JWT authorizer integration, and 6 common mistakes.
Article #94 covers the three API types (REST $3.50/M, HTTP $1.00/M, WebSocket), Lambda integrations, authorization patterns (JWT, Lambda authorizer, IAM), throttling, caching, CORS, custom domains, and why HTTP API is the right default.
Article #93 covers tool use, ReAct pattern, memory (short-term, long-term, summarization), plan-then-execute with replanning, guardrails (input/output/human-in-the-loop), multi-agent architectures (router, supervisor), Bedrock Agents, and evaluation.
Every API needs pagination. Covers offset (simple but fragile), cursor-based (stable, O(1)), and keyset (maximum performance). Plus Relay Connection spec, DynamoDB LastEvaluatedKey, SOQL OFFSET, Elasticsearch search_after, and the fetch+1 trick.
The 90th article! Covers the inverted pyramid (conclusion first), writing for scanning, README templates, ADRs, runbooks for 3 AM, API docs, code comments, writing RFCs with options and tradeoffs, changelog patterns, and onboarding docs.
Krishna's Tech Blog reached 90 articles covering Salesforce, AWS, AI/ML, and general engineering. The Learning section now has 57 flashcard decks with 1,140 cards, 310 quiz questions, and 20 certification study guides. 70 glossary terms. 9 article series.
The four staff engineer archetypes, influence radius shift, writing RFCs, mentoring without micromanaging, navigating ambiguity, cross-team influence, picking the right battles, managing technical debt strategically, and the promotion trap.
Data Cloud as a CDP: DMOs and DLOs, four ingestion methods, identity resolution with match and reconciliation rules, segmentation, activation targets, and why Data Cloud is the foundation for Agentforce and all Salesforce AI.
The four DR strategies (backup-restore to multi-site active-active), Aurora Global Database, DynamoDB Global Tables, Route 53 failover, game days with AWS FIS, runbooks, and the cost tradeoffs that drive DR decisions.
The Learning section hit major milestones: 300 multiple-choice quiz questions across Salesforce, AWS, and General topics. 56 flashcard decks with 1,120 cards. 20 certification study guides. Spaced repetition, smart review, and daily deck picks.
Strangler fig pattern, characterization tests, safe refactoring steps (extract method, dependency injection), feature flags for migration, the boy scout rule, and when to actually rewrite vs incrementally improve.
set -euo pipefail, cleanup traps, lock files with stale PID detection, getopts argument parsing, retry logic, cron job setup, ShellCheck linting, and a complete production-ready template script.
The prompt -> RAG -> fine-tune decision tree, LoRA and QLoRA for parameter-efficient training, data preparation patterns, SageMaker and Bedrock custom models, evaluation metrics, real cost breakdown, and 5 common mistakes.
Event buses, content-based pattern matching, targets (Lambda, SQS, Step Functions, API Destinations), Scheduler, Pipes, archive and replay, EventBridge vs SQS vs SNS decision framework, and 6 common mistakes.
EC2 ASGs, target tracking vs step vs scheduled scaling, ECS auto scaling, Lambda concurrency, DynamoDB capacity modes, warm pools, predictive scaling, cost optimization with Spot instances, and the multi-layer scaling problem.
Silo, pool, and bridge isolation models, database strategies, tenant context middleware with AsyncLocalStorage, automatic query scoping, PostgreSQL RLS, noisy neighbor mitigation, and onboarding automation.
Every engineer learns SOLID in interview prep and forgets it in production. This article covers all five principles with TypeScript code examples, bad/good comparisons, and honest guidance on when each principle is worth the overhead and when it creates unnecessary complexity.
Idempotency keys, retry-safe payment processing, DynamoDB conditional writes, and distributed idempotency across microservices. Includes FastAPI + Redis implementation, testing strategies, and the mistakes that cause double charges.
JSON structured logging, correlation IDs for distributed tracing, Python structlog and Node.js pino code examples, CloudWatch Logs Insights queries, log aggregation pipelines, and the mistakes that make logs useless at 3 AM.
Separate deploying code from releasing features. Covers flag types (release, ops, experiment, permission), percentage rollouts with deterministic hashing, AWS AppConfig, kill switches, flag debt, and the cleanup strategy that actually works.
For new integrations, Salesforce now recommends using External Client Apps instead of Connected Apps. Connected Apps still work but External Client Apps provide better lifecycle management and security controls.
New certification validating expertise in building and deploying AI agents with Agentforce. Covers agent configuration, prompt templates, action libraries, and guardrails. $200 exam fee.
Hyperforce expanded to over 38 global regions in 2025, up from 4 at launch, with 90% of Salesforce customers now eligible for migration. New regions include additional Asia Pacific and European data centers, giving customers greater control over data residency and compliance.
Salesforce renamed Einstein Copilot to Agentforce as part of its broader shift toward autonomous AI agents, with the feature now appearing in Setup as Agentforce (Default). No functionality changed, but UI labels, permissions, and help documentation were updated to reflect the new branding introduced at Dreamforce 2024.
Aurora Serverless v2 can now scale down to 0 ACUs, automatically pausing the database after a configurable idle period with no compute charges while paused. This resolves a long-standing gap between v1 and v2, making Aurora Serverless v2 a true pay-per-use option for dev and test workloads.
Salesforce launched Foundations, a free upgrade available to all Sales Cloud and Service Cloud Enterprise Edition and above customers, bundling Data Cloud, Marketing, Commerce, and cross-department features at no additional license cost. The Data Cloud allotment includes 10,000 segmentation and activation credits, automatic data harmonization for AI readiness, and a unified customer profile that feeds Agentforce. Email campaigns are included up to 2,000 sends per month. Foundations replaces the need to purchase separate Data Cloud licenses for customers who want basic data unification without a full Data Cloud contract.
As Salesforce migrated customer orgs to Hyperforce, Apex workloads benefit from elastic compute scaling, faster sandbox provisioning via Quick Clone, and zero-downtime major release upgrades introduced in Summer '24. Orgs on Hyperforce also gain access to Apex Guru and Scale Center, AI-powered tools that detect and surface code-level performance anti-patterns at runtime.
At Dreamforce 2023, Salesforce announced the Einstein 1 Platform, a rebrand and architectural consolidation of its core product suite around three pillars: Data Cloud for real-time customer data unification, Einstein AI for predictions and generative capabilities, and Flow for automation. Data Cloud was included at no additional cost for Enterprise Edition and above customers. Einstein Copilot Studio was introduced as a low-code builder for custom prompts, skills, and AI models. The Einstein 1 branding unified what had previously been marketed as separate products -- Tableau, MuleSoft, Slack, and the core CRM -- under a single platform narrative backed by the Salesforce metadata framework.
