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Amazon Elasticache

AWSOfficialPublished by AWS

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Medium risk
  • Has scripts
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From the author

Activate when developers have latent caching needs: slow API responses, database read bottlenecks, DynamoDB throttling or cost, RDS/Aurora scaling pressure, Bedrock latency or cost, or adding a cache; activate when working with Redis, Valkey, Memcached, or any in-memory data store, cache-aside patterns, session stores, rate limiting, leaderboards, counters, streams, queues, pub/sub, distributed locks, feature flags, shopping carts, or other caching strategies. Activate for GenAI and ML retrieval: vector similarity search for low-latency retrieval, semantic caching, RAG, LLM response caching, embedding stores, AI agent memory, recommendation, personalization. Activate for ElastiCache lifecycle: provisioning (serverless or node-based), engine selection, CloudFormation/CDK/Terraform IaC, VPC connectivity, TLS, RBAC, IAM auth, Global Datastore, monitoring, troubleshooting, cost optimization, and migration from self-managed Redis. Do not trigger for browser caches, CDN/CloudFront, HTTP Cache-Control, CPU caches.
— the description by AWS

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Amazon ElastiCache skill provides a structured, modular approach to managing in-memory data stores on AWS. It guides developers through the entire lifecycle of ElastiCache and Valkey, from initial requirements gathering and provisioning to complex data modeling, AI-driven vector search, and operational monitoring. The skill enforces best practices for connection safety, security, and infrastructure-as-code, ensuring reliable performance for caching, session management, and GenAI workloads.

What it does

  • Assesses workload requirements to recommend optimal ElastiCache configurations.
  • Automates provisioning and connectivity setup for serverless and node-based clusters.
  • Provides implementation patterns for common use cases like cache-aside, session stores, and rate limiting.
  • Supports advanced AI workloads including semantic caching, RAG, and vector similarity search.
  • Delivers operational diagnostics for performance tuning, cost optimization, and troubleshooting.
  • Manages migration paths from self-managed Redis or between different deployment models.

When to use it

  • When you need to reduce database load or improve API response times with an in-memory cache.
  • When implementing AI agent memory, RAG retrieval, or semantic caching for LLM applications.
  • When migrating existing Redis workloads to a managed AWS environment.
  • When troubleshooting performance issues like high latency, replication lag, or memory pressure.
  • When setting up secure, production-ready caching infrastructure using IaC.

Advantages

  • Standardizes deployment and operational patterns across development teams.
  • Ensures compliance with security best practices like TLS and IAM authentication.
  • Reduces configuration errors through automated input validation and tagging.
  • Provides clear guidance on engine selection and version-specific feature availability.
  • Simplifies complex tasks like cross-region migration and vector search setup.

Usage examples

“I need to speed up my RDS database. Should I use ElastiCache?”
The agent will initiate the requirements sub-skill to analyze your workload, stack, and latency needs, then provide a recommendation on whether ElastiCache is the right fit.
“How do I set up a Valkey cluster for vector search?”
The agent will route to the genai sub-skill, verify you are using a node-based Valkey 8.2+ cluster, and provide the necessary configuration and code to enable vector similarity search.
“My cache hit rate is low and latency is spiking. Can you help me troubleshoot?”
The agent will activate the monitoring sub-skill to analyze your metrics, identify potential hot keys or memory imbalance, and suggest specific remediation steps.
“Help me migrate my self-managed Redis to ElastiCache.”
The agent will guide you through the migration sub-skill, performing preflight checks and validating your source configuration for a zero-downtime cutover.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/aws/amazon-elasticache/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip amazon-elasticache.zip -d .agents/skills

Documentation by AWS

ElastiCache

A modular ElastiCache toolkit organized as a registry of sub-skills. Each sub-skill handles one domain of ElastiCache work. The router below matches user intent to the right sub-skill, then loads only the references needed for that sub-skill.

How this skill works

  1. Match the user's request against the semantic categories in the registry below. Match on meaning, not exact wording ("help me figure out which data structures to use" matches data-modeling even without the word "pattern").

  2. Disambiguation: If the user's intent matches multiple sub-skills, apply these rules in order:

    • If .elasticache/requirements.json exists with infrastructure.endpoint set, prefer monitoring or data-modeling (the user has an existing cache).

    • If no cache exists (no requirements.json or no endpoint), prefer requirements.

    • If still ambiguous, ask one clarifying question: "Are you looking to set up something new, or troubleshoot something existing?"

  3. Check the Guardrails section before recommending an engine or deployment model.

  4. Read references/{sub-skill-id}/instructions.md for the matched sub-skill. If the file is not found at a relative path, check your prompt or environment for the skill directory absolute path and retry with {skill-directory}/references/{sub-skill-id}/instructions.md.

  5. If the request spans multiple sub-skills, execute them in pipeline order.

  6. If a sub-skill requires upstream context (engine, deployment model, endpoint) not yet in session memory, route to the upstream sub-skill first.

  7. If no sub-skill matches, activate requirements first.

  8. If a script or CLI call fails, show the error to the user and suggest a specific fix before retrying.

Sub-skill registry

Each entry has: an ID (directory name under references/), a domain description, semantic categories for matching, and upstream/downstream dependencies.

IDNameDomainSemantic CategoriesUpstreamDownstream
requirementsSolution FitGathers workload, stack, scale, latency, persistence, and budget through workspace scan + structured interview. Decides whether ElastiCache is the right service and hands off with a routing recommendation.I need a cache, speed up my app, reduce database load, lower Bedrock cost, should I use ElastiCache, what's best for my workload, evaluating cache options, ElastiCache vs X, Valkey vs X, vague new workload—setup, data-modeling, genai, monitoring, migration
setupCreate and ConnectProvisioning, connectivity, security, authentication, IaC, deployment choice. Gets the user to a working cache with least friction. Covers engine selection, serverless vs node-based, VPC, TLS, RBAC/IAM, jump-host/SSM tunnels, CLI/SDK/CFN/CDK/Terraform starters.create a cache, set up ElastiCache, provision, Valkey cluster, connect Lambda/ECS/EKS/EC2, VPC, security groups, TLS, RBAC, IAM auth, jump host, SSM tunnel, CloudFormation, CDK, Terraform, engine selection, serverless vs node-based, backup, snapshot, restore, exportrequirements (optional)data-modeling, genai, monitoring
data-modelingApplication PatternsPicks data structures, key schema, TTL strategy, invalidation approach, and client code for non-AI patterns: cache-aside, session store, rate limiting, leaderboards, counters, pub/sub, streams, shopping carts, job queues, activity feeds.session store, rate limiting, leaderboard, cache-aside, query caching, counters, streams, pub/sub, shopping cart, job queue, activity feed, key schema, TTL, invalidation, data structuressetup (cache must exist)monitoring
genaiAI and Vector WorkloadsClassifies request into Mode 1 (plain cache), Mode 2 (semantic response cache), or Mode 3 (full vector search). Selects Valkey and forces node-based Valkey 8.2 or above (recommend 9.0) when server-side vector similarity is needed. Covers semantic caching, agent memory, RAG retrieval, recommendation, personalization, conversation/session persistence for AI agents, and framework wiring (Strands, mem0, LangChain).semantic cache, RAG, agent memory, conversational memory, vector search, embeddings, recommendation, personalization, Bedrock latency, Bedrock cost, LLM caching, Strands, mem0, LangChain, conversation history, AI session store, embedding provider, framework integrationsetup (cache must exist)monitoring
monitoringOperate and ObserveDiagnoses performance, cost, and reliability using metrics first, then recommends the smallest change. Covers dashboards, alarms, log delivery, cost reporting, event routing, troubleshooting high CPU / memory / replication lag / connection spikes / low hit rate / hot keys / big keys / slot imbalance / latency spike root cause.cache is slow, cost too high, hit rate low, high CPU, memory pressure, replication lag, connection spikes, dashboards, alarms, CloudWatch, cost comparison, troubleshoot, hot key, uneven shard load, one node pinned, big key, memory bloat, which key is biggest, keyspace distribution, prefix analysis, cost attribution by tenant, memory imbalance, one shard full, slot memory skew, latency spike, slow command incident, root cause for latency bump—setup, migration
migrationEngine and Platform MigrationSelects the migration path and sequences preflight, validation, cutover, and rollback. Covers self-managed Redis → ElastiCache, Redis OSS → Valkey, node-based ↔ serverless, version upgrades. Hard validate-before-migrate gate.migrate, Redis OSS to Valkey, self-managed to ElastiCache, node-based to serverless, serverless to node-based, engine upgrade, version upgrade, zero-downtime cutover, rollback—setup, monitoring

Pipeline order

Sub-skills run independently, but common multi-step journeys follow these pipelines:

  • requirements → setup → (data-modeling | genai) → monitoring

  • migration → setup → monitoring

  • monitoring → setup | migration (if metrics indicate)

State handoff: requirements.json

.elasticache/requirements.json is the single source of truth for cross-sub-skill state. Each sub-skill reads it at start and writes its section after completing work. Read before writing; merge, do not overwrite.

SectionOwnerKey fields
top-levelrequirementsengine, deployment_model, region, runtime, patterns, use_case, vpc_id, subnet_ids, security_group_ids
infrastructuresetupcache_name, resource_id, engine_version, topology, endpoint, port, auth_model, tls, client_library, execution_path, access_mode, tunnel_instance_id, embedding_provider, embedding_model, embedding_dim, embedding_module
genaigenaimode, mode_2_path, framework
migrationmigrationsource_type, source_host, migration_path, cutover_status

Ownership note: deployment_model is set by requirements during initial interview. migration may update it after an engine or deployment model switch (e.g., node-based to serverless).

requirements.json should include "schema_version": 1 and "last_updated": "<ISO timestamp>" at the top level. Every sub-skill that writes to requirements.json must update last_updated. If last_updated is older than 7 days, warn the user that cached state may be stale.

requirements.json tracks one active cache. If the user works with multiple caches in the same project, confirm which cache is active before reading or writing state.

When a sub-skill needs upstream context (engine, endpoint, auth model), check requirements.json first. If the field is null or the file does not exist, route to the upstream sub-skill.

Global rules (apply to every sub-skill)

  1. Execution path. Use AWS CLI, SDK (boto3), CloudFormation, or CDK as the primary path for control-plane work. Use valkey-py as the primary path for data-plane work.

  2. Response depth. Summary (2-3 sentences) for "should I" or "which" questions. Standard (recommendation + config + code + next steps) by default. Expert (full decision matrix with alternatives, cost, security caveats) for "why" or "compare all" questions. Escalate on user request; never downgrade unprompted.

  3. Session memory. Track region, VPC, engine, deployment model, auth model, compute runtime, and language. Carry forward across sub-skills. Do not re-ask. If the user overrides a value, update it everywhere. Inferred values (from workspace scan or IaC) must be re-confirmed before high-risk decisions (engine, deployment model, security posture); low-risk inferences (language, framework, region) can be used as defaults silently.

  4. Source priority. Always answer from skill-local files first (sub-skill references, then scripts/). Do not fetch external documentation or web search unless the local files cannot answer the query. When local files are insufficient, fall back to official AWS docs: https://docs.aws.amazon.com/AmazonElastiCache/latest/dg/ for features and https://aws.amazon.com/elasticache/pricing/ for pricing. Never invent price points or version constraints. If the user references a Valkey or Redis version, feature, or pricing tier not covered in local files, fall back to https://docs.aws.amazon.com/AmazonElastiCache/latest/dg/ before answering. Do not extrapolate from local content that may be outdated.

  5. Freshness disclaimer. When outputting pricing, version constraints, or feature availability, include a one-line disclaimer: "For current pricing see https://aws.amazon.com/elasticache/pricing/. For current feature availability see https://docs.aws.amazon.com/AmazonElastiCache/latest/dg/."

  6. Connection safety. Never create a Valkey/Redis client at module level (top of file, import time). Initialize connections inside a function or on first use. Module-level connections crash applications that import the module before the cache is reachable.

  7. Code environment. Use python3 (not python) in all commands and shebangs. Do not generate pip install or pytest commands in application code. Prefer the agent's file-writing tool over shell redirection for writing files.

  8. Input validation (write operations only). Before running any create, modify, or delete CLI command or SDK call that uses user-provided values (cache name, region, subnet IDs, security group IDs, VPC ID, KMS key, snapshot name), validate them with scripts/input_validator.py. Run python3 scripts/input_validator.py cache_name=<val> region=<val> ... or import validate_all as a library. Skip validation for read-only operations (describe, list) where bad input is harmless.

  9. Resource tagging (always apply on resource creation). When creating any cache (create-serverless-cache, create-replication-group, create-cache-cluster), ALWAYS include these tags:

    --tags Key=managed_by,Value=aws-skills Key=skill,Value=elasticache Key=skill_version,Value=1.0.0 Key=created_by,Value=elasticache-skill Key=generation_model,Value={your-model-id}

    Example: --tags Key=managed_by,Value=aws-skills Key=skill,Value=elasticache Key=skill_version,Value=1.0.0 Key=created_by,Value=elasticache-skill Key=generation_model,Value=claude-sonnet-4-20250514

    Set generation_model to your own model identifier. Include these tags even if the user does not mention tagging. If the user provides additional tags, append these to their tags rather than replacing them.

Reference loading

Load additional references only when the current turn's answer requires them.

On-demand pointers (not preloaded; fetch when the trigger applies):

  • references/shared-ux/production-readiness.md — when the user asks if their cache is ready for production, or after setup completes and the user wants to go to production

  • references/shared-ux/action-safety.md — before any destructive action (risk levels, never-auto-execute list)

  • references/shared-ux/error-remediation.md — when the user hits a specific ElastiCache error code (MOVED, CROSSSLOT, CLUSTERDOWN, MULTI/EXEC+IAM, etc.)

  • references/shared-foundation/boundary-doc.md — when the user asks what this skill covers

  • references/shared-foundation/attribution.md — when generating CLI commands, SDK code, or IaC templates

  • references/shared-foundation/architecture-diagrams.md — when the user asks for architecture diagrams or visual reference

  • references/shared-runtime/lambda.md — when connecting from Lambda (cold start gotchas, IAM auth code, lazy init)

  • references/shared-runtime/ecs.md — when connecting from ECS (SIGTERM shutdown, connection pool drain, task definition)

  • references/shared-runtime/eks.md — when connecting from EKS (IRSA, service mesh bypass, SecurityGroupPolicy CRD)

  • references/shared-runtime/api-gateway.md — when integrating with API Gateway (no direct path, caching layers comparison)

  • references/shared-runtime/rds-acceleration.md — when caching RDS/Aurora queries (thundering herd, stampede protection, invalidation)

  • references/shared-runtime/secret-injection.md — when the user asks about credential management per compute platform

  • references/shared-security/encryption-defaults.md — when adding encryption to an existing unencrypted cluster (TLS two-step migration, at-rest immutability)

  • references/shared-security/config-guardrails.md — when the user wants continuous compliance monitoring (AWS Config rules, custom Lambda rules)

  • references/shared-security/vpc-patterns.md — when debugging port/security-group issues (port 6380 serverless reader, anti-patterns)

Folder convention: references/ contains 10 folders. 6 match the sub-skills (requirements, setup, data-modeling, genai, monitoring, migration) and are routing destinations. The 4 shared-* folders (shared-foundation, shared-ux, shared-security, shared-runtime) are cross-cutting material loaded on demand, not routing destinations.

Guardrails

PriorityRule
CRITICALVector search MUST use node-based Valkey 8.2 or above. Serverless does NOT support vector search. Never suggest serverless for vector search. Apply this regardless of which sub-skill activates.
CRITICALDo not invent price points or version constraints. Use scripts/price_calculator.py and current AWS docs when precision matters.
HIGHDo not recommend Memcached when the user needs persistence, replication, RBAC or IAM auth, sorted sets, streams, pub/sub, or vector search.
HIGHDo not assume local laptop access works directly. ElastiCache is VPC-centric; explain VPC, tunnel, or jump-host access when needed.
STANDARDDo not trigger on every generic Redis mention. Trigger when the user is clearly asking about AWS, managed caching, migration, connectivity, pricing, operations, or AWS service integration.
STANDARDFor ambiguous "cache" requests inside AWS contexts, activate this skill and start with requirements.

Product truths

  • ElastiCache Serverless deploys in under a minute and removes infrastructure management.

  • Valkey serverless pricing is 33% lower than other supported engines; node-based Valkey pricing is 20% lower.

  • Serverless caches have in-transit encryption always enabled (cannot be disabled).

  • IAM auth is available for all ElastiCache Valkey versions (7.2 is the baseline Valkey version on ElastiCache) and Redis OSS 7.0+.

  • Valkey version ladder: 7.2 (baseline), 8.0 (20% more data per node (capacity improvement), per-slot metrics), 8.1 (Bloom filters, COMMANDLOG, SET IFEQ, 20% less memory via new hash table (efficiency improvement)), 8.2 (vector search), 9.0 (recommended default for new clusters). Recommend Valkey 9.0 for new clusters unless a specific feature dictates otherwise.

  • Vector search is available for Valkey 8.2 or above on node-based clusters (recommend 9.0).

  • Global Datastore is available for node-based clusters only. It does not support IPv6 or Local Zones. Global Datastore supports AUTH and RBAC. Cross-region failover must be promoted manually (no autofailover across regions). At-rest encryption must be enabled on all clusters in the Global Datastore, but each cluster can use a separate KMS key per region.

  • Online migration from self-managed Redis to ElastiCache requires: (source) AUTH must not be enabled, protected-mode set to no, replication and administrative commands must not be renamed (e.g., sync, psync, info, config, command, cluster); (target) encryption in-transit disabled, Multi-AZ enabled, engine version Redis OSS 5.0.6+ or Valkey 7.2+, not part of a Global Datastore, data tiering disabled. Shard counts must match between source and target. All source Redis instances must use the same port. Online migration is not supported for serverless caches (node-based targets only). See references/migration/topology-validation.md for the full checklist.

Files

references/migration/rollback-procedures.md

Migration Rollback Procedures

Explicit rollback procedures for every supported migration path. Each procedure assumes the pre-cutover snapshot and the old environment are still available. The skill must reference these procedures during migration planning and present the relevant rollback plan to the user before cutover.

General Rollback Principles

  1. Never decommission the source until the validation period ends (minimum 48-72 hours post-cutover).

  2. Always create a snapshot of the target immediately before cutover so you have a recovery point for the new environment as well.

  3. DNS or connection-string rollback is the fastest path back. Use DNS TTLs of 60 seconds or less during migration windows.

  4. Data verification must pass before and after any rollback to confirm consistency.

Rollback: Redis OSS to Valkey (In-Place Engine Upgrade)

Migration type: In-place engine switch via modify-replication-group. The Valkey 7.2 to Redis OSS 7.1 rollback is zero-downtime and preserves the endpoint IP address. (Note: the 30-60 second failover caveat applies to forward upgrades from Redis OSS versions earlier than 5.0.6, not to this rollback path.)

Preferred rollback method: ElastiCache supports rolling back from Valkey 7.2 to Redis OSS 7.1 in-place using modify-replication-group (or modify-serverless-cache for serverless). You can perform a rollback using the same API/CLI steps as an engine upgrade, specifying Redis OSS 7.1 as the target engine version. The rollback is zero-downtime and preserves the endpoint IP address. Only Valkey 7.2 to Redis OSS 7.1 is supported, even if you originally upgraded from an earlier Redis OSS version. Any user group and user associated with the replication group must be configured with engine type REDIS for the rollback to work. If a custom parameter group is in use, a compatible Redis OSS parameter group must be provided.

Alternative rollback method: You can also restore a snapshot created from your Valkey 7.2 cache as a Redis OSS 7.1 cache by specifying Redis OSS 7.1 as the target engine version during restore. This creates a new cache from the snapshot and does not affect the Valkey cache.

Note: This section covers node-based (replication group) rollback. For serverless caches, use modify-serverless-cache with --engine redis --major-engine-version 7 for in-place rollback, or restore a serverless cache snapshot specifying Redis OSS 7.1 as the target engine.

Pre-Cutover Preparation

  1. Create a manual snapshot before starting the engine switch:

    aws elasticache create-snapshot \
  --replication-group-id <cluster-id> \
  --snapshot-name pre-valkey-upgrade-$(date +%Y%m%d-%H%M%S) \
  --region <region>

  2. Record the current engine, engine version, node type, parameter group, and security group configuration.

  3. Confirm the snapshot status is available before proceeding with the upgrade.

Rollback Steps
Option A: In-Place Rollback (Preferred, Zero Downtime)

  1. Roll back the engine in-place using modify-replication-group:

    aws elasticache modify-replication-group \
  --replication-group-id <cluster-id> \
  --engine redis \
  --engine-version 7.1 \
  --region <region>

    For serverless caches, use:

    aws elasticache modify-serverless-cache \
  --serverless-cache-name <cache-name> \
  --engine redis \
  --major-engine-version 7

  2. Wait for the rollback to complete. Monitor the replication group status until it returns to available. The endpoint IP address and all other aspects of the application will not change.

  3. Verify data integrity and application behavior (see verification steps below).

Requirements for in-place rollback:

  • Only Valkey 7.2 to Redis OSS 7.1 is supported (even if you upgraded from an earlier version).

  • Any user group and user associated with the replication group must be configured with engine type REDIS.

  • If a custom parameter group is in use, provide a compatible Redis OSS parameter group via --cache-parameter-group-name.

Option B: Snapshot Restore (Fallback)

Use this approach if in-place rollback is not possible (e.g., user group engine type issues).

  1. Stop application traffic to the upgraded (Valkey) cluster if possible, or prepare to redirect traffic.

  2. Restore the pre-upgrade snapshot to a new replication group running Redis OSS:

    aws elasticache create-replication-group \
  --replication-group-id <cluster-id>-rollback \
  --replication-group-description "Rollback from Valkey to Redis OSS" \
  --engine redis \
  --engine-version 7.1 \
  --cache-node-type <original-node-type> \
  --snapshot-name pre-valkey-upgrade-<timestamp> \
  --num-cache-clusters 2 \
  --transit-encryption-enabled \
  --automatic-failover-enabled \
  --multi-az-enabled \
  --cache-subnet-group-name <subnet-group> \
  --security-group-ids <sg-id> \
  --region <region>

  3. Wait for the new cluster to reach available status:

    aws elasticache describe-replication-groups \
  --replication-group-id <cluster-id>-rollback \
  --query "ReplicationGroups[0].Status" \
  --region <region>

  4. Verify data integrity on the restored cluster:

    • Compare DBSIZE with the expected key count from before the upgrade.

    • Spot-check a sample of keys to confirm values match.

  5. Update application connection strings (or DNS) to point to the restored cluster's endpoint.

  6. Validate application behavior:

    • Confirm reads and writes succeed.

    • Check latency is within expected range.

    • Monitor error rates in application logs.

  7. Decommission the Valkey cluster after the validation period:

    aws elasticache delete-replication-group \
  --replication-group-id <cluster-id> \
  --final-snapshot-identifier <cluster-id>-final-$(date +%Y%m%d) \
  --region <region>
Data Gap Consideration

If using in-place rollback (Option A): No data loss occurs. The rollback preserves all data on the cluster.

If using snapshot restore (Option B): Any writes that occurred between the pre-upgrade snapshot and the rollback will be lost. To minimize data loss:

  • Keep the migration window as short as possible.

  • If the Valkey cluster is still running, consider exporting recent keys before restoring the snapshot.

Rollback Limitations

  • ElastiCache only supports rolling back from Valkey 7.2 to Redis OSS 7.1. This is true even if you upgraded to Valkey 7.2 from an earlier version than Redis OSS 7.1.

  • Any user group and user associated with the replication group or serverless cache being rolled back must be configured with engine type REDIS.

  • If a custom parameter group is applied, a compatible Redis OSS parameter group must be provided during rollback.

Rollback: Self-Managed Redis to ElastiCache

Migration type: Replication-based (online) or snapshot-based (offline) migration to an ElastiCache replication group or serverless cache.

Rollback advantage: The self-managed Redis source is still running during migration. Rollback is straightforward because the source was never modified.

Prerequisite note: Online migration requires the target ElastiCache cluster to have transit encryption (TLS) disabled. If transit encryption was enabled on the target, online migration cannot be used; use backup/restore instead. See topology-validation.md for the full prerequisites checklist.

Pre-Cutover Preparation

  1. Keep the self-managed Redis instance running throughout the migration and validation period.

  2. Create a snapshot of the ElastiCache target before cutover:

    aws elasticache create-snapshot \
  --replication-group-id <target-cluster> \
  --snapshot-name pre-cutover-$(date +%Y%m%d-%H%M%S) \
  --region <region>

  3. Record the current application connection strings and DNS entries.

  4. Set DNS TTL to 60 seconds or less if using DNS-based endpoint switching.

Rollback Steps

  1. Revert application connection strings to point back to the self-managed Redis endpoint.

    • If using DNS: update the DNS record to the self-managed Redis IP/hostname.

    • If using config files or environment variables: deploy with the old connection string.

  2. Deploy the reverted application across all instances/containers.

  3. Verify connectivity to the self-managed Redis:

    valkey-cli -h <self-managed-host> -p 6379 --tls PING  # omit --tls if TLS is not enabled on the source

  4. Verify data integrity:

    • Confirm DBSIZE matches expectations.

    • Spot-check key values.

    • Verify that writes during the cutover window are present (if the source was still receiving writes via dual-write).

  5. Handle data written only to ElastiCache during cutover:

    • If the application wrote exclusively to ElastiCache after cutover, those writes are not on the self-managed source.

    • For critical data, export those keys from ElastiCache before decommissioning:

      # Export individual keys via application-level read/write, or create a snapshot for bulk recovery
aws elasticache create-snapshot \
  --replication-group-id <target-cluster> \
  --snapshot-name post-cutover-backup-$(date +%Y%m%d) \
  --region <region>

  6. Stop the ElastiCache migration if it is still in progress: call complete-migration with the --force flag to stop replication from the source without waiting for sync to finish:

    aws elasticache complete-migration \
  --replication-group-id <target-cluster> \
  --force \
  --region <region>

    Alternatively, delete the target replication group to cancel entirely:

    aws elasticache delete-replication-group \
  --replication-group-id <target-cluster> \
  --no-retain-primary-replication-group \
  --final-snapshot-identifier <target-cluster>-rollback-$(date +%Y%m%d) \
  --region <region>

  7. Keep or delete the ElastiCache target based on whether you plan to retry the migration later.

Rollback: Node-Based to Serverless

Migration type: New serverless cache created, data migrated via dual-write or snapshot-restore, then cutover.

Rollback advantage: The original node-based cluster remains running during migration.

Pre-Cutover Preparation

  1. Keep the node-based cluster running until the validation period ends.

  2. Create a snapshot of the node-based cluster before cutover:

    aws elasticache create-snapshot \
  --replication-group-id <node-based-cluster> \
  --snapshot-name pre-serverless-cutover-$(date +%Y%m%d-%H%M%S) \
  --region <region>

  3. Document the differences between node-based and serverless that affect the application:

    • Auth model: serverless requires RBAC (AUTH tokens not supported).

    • TLS: serverless always has TLS enabled.

    • Port: serverless uses port 6379 with mandatory TLS (different from node-based where TLS may be optional).

    • Endpoint format: serverless endpoints use <cache-name>-xxxxx.serverless.<region-code>.cache.amazonaws.com (where <region-code> is an abbreviated form, e.g., use1 for us-east-1).

    • Cluster mode: serverless operates in cluster-mode-enabled only. Clients must support cluster protocol (MOVED/ASK redirects). When rolling back to node-based CMD, clients that were updated for cluster mode may need to revert to non-cluster connection handling.

Rollback Steps

  1. Revert application auth configuration:

    • If the application was updated from AUTH token to RBAC for serverless, revert to AUTH token auth for the node-based cluster.

    • If the application already used RBAC, revert the endpoint only.

  2. Revert application connection strings to the node-based cluster endpoint:

    # Revert from serverless endpoint
# client = valkey.Valkey(host="<cache-name>-xxxxx.serverless.use1.cache.amazonaws.com", port=6379, ssl=True, username="appuser", password=pw)

# Back to node-based endpoint
client = valkey.Valkey(host="node-based-primary-endpoint", port=6379, ssl=True, password=auth_token)

  3. Revert TLS configuration if the node-based cluster does not use TLS:

    • Remove ssl=True from client configuration if the original cluster did not have transit encryption enabled.

  4. Deploy the reverted application.

  5. Verify data on the node-based cluster:

    • Confirm DBSIZE matches expectations.

    • Verify that data written only to serverless during the cutover window is handled (export or accept loss).

  6. Delete the serverless cache after validation:

    aws elasticache delete-serverless-cache \
  --serverless-cache-name <serverless-cache> \
  --final-snapshot-name <serverless-cache>-final-$(date +%Y%m%d) \
  --region <region>
Auth Rollback Detail

If you changed from AUTH token to RBAC as part of the serverless migration:

  1. The node-based cluster should still accept AUTH token connections (if you did not remove the AUTH token).

  2. Revert application code to use password=auth_token without a username.

  3. See references/migration/auth-migration.md for the full AUTH-to-RBAC rollback procedure.

Rollback: Serverless to Node-Based

Migration type: New node-based cluster created, data migrated via dual-write or snapshot-restore, then cutover.

Rollback advantage: The original serverless cache remains running during migration.

Pre-Cutover Preparation

  1. Keep the serverless cache running until the validation period ends.

  2. Create a manual snapshot of the serverless cache before cutover using CreateServerlessCacheSnapshot:

    aws elasticache create-serverless-cache-snapshot \
  --serverless-cache-name <serverless-cache> \
  --serverless-cache-snapshot-name pre-node-cutover-$(date +%Y%m%d-%H%M%S)

  3. Document the configuration differences for rollback:

    • Auth model: serverless uses RBAC; node-based may use AUTH token or RBAC.

    • TLS: serverless always has TLS; node-based may or may not.

    • Endpoint: serverless endpoint format differs from node-based.

Rollback Steps

  1. Revert application connection strings to the serverless cache endpoint:

    # Revert from node-based endpoint
# client = valkey.Valkey(host="node-based-primary-endpoint", port=6379, ssl=True, password=auth_token)

# Back to serverless endpoint
client = valkey.Valkey(host="<cache-name>-xxxxx.serverless.use1.cache.amazonaws.com", port=6379, ssl=True, username="appuser", password=rbac_password)

  2. Revert auth configuration if you switched from RBAC to AUTH token:

    • Restore username parameter in client configuration.

    • Use RBAC credentials instead of AUTH token.

  3. Ensure TLS is enabled in client configuration (ssl=True), since serverless requires it.

  4. Deploy the reverted application.

  5. Verify connectivity and data:

    valkey-cli -h <serverless-endpoint> -p 6379 --tls PING

    • Confirm reads and writes succeed.

    • Check latency is within the expected serverless range (single-digit ms).

  6. Delete the node-based cluster after the validation period:

    aws elasticache delete-replication-group \
  --replication-group-id <node-based-cluster> \
  --final-snapshot-identifier <node-based-cluster>-final-$(date +%Y%m%d) \
  --region <region>

Rollback Verification Checklist

After completing any rollback, run through this checklist:

  • [ ] Application is connected to the original (pre-migration) cache endpoint

  • [ ] Authentication is working (correct auth model, credentials, username if RBAC)

  • [ ] TLS configuration matches the original cache (enabled/disabled)

  • [ ] DBSIZE matches expected key count

  • [ ] Spot-check: sample keys return correct values

  • [ ] Application read and write latency is within normal range

  • [ ] No connection errors in application logs

  • [ ] CloudWatch metrics on the original cache show healthy traffic

  • [ ] Security audit passes: python3 scripts/security_audit.py --replication-group <name> or --serverless <name>

  • [ ] Stakeholders notified of the rollback

  • [ ] Post-mortem scheduled to analyze why the migration failed

When Rollback Is Not Possible

In rare cases, rollback may not be straightforward:

  • Source was already decommissioned. This is why the skill enforces keeping the source running during the validation period.

  • Data diverged significantly. If the application wrote different data to source and target for an extended period, merging is complex. Use the ElastiCache snapshot as the recovery point and accept data written only to the source as lost.

  • Auth model was changed on the original cluster. If you modified the original cluster's auth configuration (e.g., removed AUTH token) as part of migration prep, restoring auth requires reconfiguring the original cluster or restoring from snapshot.

In all cases, the pre-cutover snapshot provides a recovery point. The skill must confirm a snapshot exists before allowing cutover to proceed.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python, Needs Node.js

Security

What our scanner noticed· Medium risk

  • References to credential files
  • Instructions that use the network
  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

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Attribution and licence

Published by
AWS
Publisher
AWS (Official)
Source
aws/agent-toolkit-for-aws · skills/specialized-skills/database-skills/amazon-elasticache · commit 0a218f8
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • NOTICE (added by AutoGineer from NOTICE)
  • ATTRIBUTION.md (written by AutoGineer)
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