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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://mp-staging.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/self-managed-migration.md

Self-Managed Redis Migration to ElastiCache

Migrate from self-managed Redis (running on EC2, on-premises, or another cloud provider) to Amazon ElastiCache. This guide covers assessment, migration approaches, and cutover.

Assessment Phase

Before migrating, inventory your source environment and validate compatibility.

1. Source Inventory

Gather the following from your self-managed Redis instance:

ItemHow to checkWhy it matters
Redis versionINFO server -> redis_versionValkey 7.2 is compatible with Redis OSS up to version 7.2.4. Older source versions may use deprecated features.
Data sizeINFO memory -> used_memory_humanDetermines target cache sizing and migration duration
Key countDBSIZEHelps estimate migration time and validate completeness
Command usageINFO commandstatsIdentifies unsupported or uncommon commands
Persistence configCONFIG GET save, CONFIG GET appendonlyDetermines whether RDB snapshots or AOF are in use for snapshot-based migration
Cluster modeINFO cluster -> cluster_enabledCluster mode affects migration tooling and target topology
Modules loadedMODULE LISTRedisJSON, RediSearch, RedisTimeSeries, etc. may not all be available in Valkey
Connected clientsINFO clients -> connected_clientsHelps size the target cache
Peak memoryINFO memory -> used_memory_peak_humanSize the target to handle peak load
Replication topologyINFO replicationIdentifies primary/replica structure to replicate on the target
2. Automated Preflight Check

Run the bundled preflight script against your source Redis:

# Without TLS
python3 scripts/migration_preflight.py --host <source-host> --port 6379

# With TLS
python3 scripts/migration_preflight.py --host <source-host> --port 6379 --tls

The script checks version compatibility, module usage, key count, memory, cluster mode, and sizing. Resolve any FAIL findings before proceeding.

3. Compatibility Check

Review potential compatibility issues:

  • Unsupported commands: Some Redis commands may behave differently or be unavailable. Check commandstats output against ElastiCache supported commands.

  • Modules: If you use RedisJSON, RediSearch, or RedisTimeSeries modules, verify whether Valkey provides equivalent functionality or plan application changes.

  • Lua scripts: Test all Lua scripts against the target engine. Most standard Lua scripts work unchanged, but scripts that use module-specific commands need updates.

  • Restricted commands: The following commands are unavailable on ElastiCache: bgrewriteaof, bgsave, config, debug, migrate, replicaof, save, slaveof, shutdown, and sync. Use parameter groups instead of CONFIG commands. Check your application code and scripts for usage of any of these commands.

4. Network Planning

ElastiCache runs inside a VPC. Plan connectivity from your source to the target:

  • Source on EC2 (same VPC): Direct access. Ensure security groups allow traffic on port 6379.

  • Source on EC2 (different VPC): Use VPC peering or Transit Gateway.

  • Source on-premises: Use AWS Direct Connect or Site-to-Site VPN for replication-based migration. For snapshot-based, upload the RDB file to S3.

  • Source on another cloud: Use VPN, Direct Connect, or snapshot-based migration via S3.

Migration Approaches

Approach 1: Snapshot-Based (Offline)

Best for: Small to medium datasets, acceptable downtime window, simplest execution.

Steps:

# 1. Create RDB snapshot on the source
valkey-cli -h <source-host> BGSAVE
# Wait for completion:
valkey-cli -h <source-host> LASTSAVE

# 2. Copy the RDB file to S3
aws s3 cp /var/lib/redis/dump.rdb s3://my-migration-bucket/dump.rdb

# 3. Grant ElastiCache access to the S3 bucket by adding a bucket policy:
# {
#   "Version": "2012-10-17",
#   "Statement": [{
#     "Sid": "ElastiCacheSnapshotAccess",
#     "Effect": "Allow",
#     "Principal": { "Service": "<region>.elasticache-snapshot.amazonaws.com" },
#     "Action": ["s3:GetObject", "s3:ListBucket", "s3:GetBucketAcl"],
#     "Resource": [
#       "arn:aws:s3:::my-migration-bucket",
#       "arn:aws:s3:::my-migration-bucket/*"
#     ]
#   }]
# }

# 4. Create an ElastiCache replication group and seed from the snapshot
aws elasticache create-replication-group \
  --replication-group-id my-new-cache \
  --replication-group-description "Migrated from self-managed Redis" \
  --engine valkey \
  --engine-version 9.0 \
  --cache-node-type cache.r7g.large \
  --num-cache-clusters 2 \
  --snapshot-arns arn:aws:s3:::my-migration-bucket/dump.rdb \
  --transit-encryption-enabled \
  --region <region>

Downtime: Equals the time from final snapshot to application cutover. For large datasets, this can be minutes to hours.

Limitations:

  • Requires a downtime window

  • Any writes during migration are lost

  • RDB format must be compatible with the target engine version

  • For node-based clusters, use --snapshot-arns with create-replication-group. For serverless caches, use --snapshot-arns-to-restore with create-serverless-cache instead.

Approach 2: Replication-Based (Online)

Eligibility: Online migration is not supported to ElastiCache serverless caches or clusters running on the r6gd node type. This approach is designed for migrating from self-hosted Redis/Valkey on EC2 to ElastiCache, not for moving data between ElastiCache clusters.

Best for: Large datasets, minimal downtime requirement, source is network-reachable from VPC.

Steps:

# 1. Create the target replication group (without snapshot seeding)
aws elasticache create-replication-group \
  --replication-group-id my-new-cache \
  --replication-group-description "Migration target" \
  --engine valkey \
  --engine-version 9.0 \
  --cache-node-type cache.r7g.large \
  --num-cache-clusters 2 \
  --automatic-failover-enabled \
  --multi-az-enabled \
  --region <region>

# 2. Test the migration (validates connectivity and compatibility)
aws elasticache test-migration \
  --replication-group-id my-new-cache \
  --customer-node-endpoint-list Address=<source-host>,Port=6379 \
  --region <region>

# 3. Start the migration (begins replication)
aws elasticache start-migration \
  --replication-group-id my-new-cache \
  --customer-node-endpoint-list Address=<source-host>,Port=6379 \
  --region <region>

# 4. Monitor replication status
# Option A: Use INFO replication on the ElastiCache primary node
# to check master_link_status (should be 'up') and replication offset
valkey-cli -h <elasticache-primary-endpoint> -p 6379 INFO replication

# Option B: Monitor the ReplicationLag and PrimaryLinkHealthStatus
# CloudWatch metrics for the target replication group
aws cloudwatch get-metric-statistics \
  --namespace AWS/ElastiCache \
  --metric-name ReplicationLag \
  --dimensions Name=CacheClusterId,Value=my-new-cache-001 \
  --statistics Average \
  --start-time $(date -u -d '10 minutes ago' +%Y-%m-%dT%H:%M:%S) \
  --end-time $(date -u +%Y-%m-%dT%H:%M:%S) \
  --period 60 \
  --region <region>

# 5. When lag is minimal, complete the migration (promotes the target)
aws elasticache complete-migration \
  --replication-group-id my-new-cache \
  --region <region>

# To abort migration without ensuring data is in sync, use --force:
# aws elasticache complete-migration \
#   --replication-group-id my-new-cache \
#   --force \
#   --region <region>
# WARNING: --force stops migration without ensuring data is in sync.
# Use it only to abort migration, not for normal completion.

Replication lag convergence: "Minimal" means ReplicationLag < 1 second for 5 consecutive checks (1 minute apart). If lag does not converge below 1s within 30 minutes, check source write rate and network bandwidth between source and target. Do not proceed with complete-migration until lag is stable.

Monitoring replication health: In addition to the CLI command above, verify replication status using:

  • Run INFO replication on the ElastiCache primary node and confirm master_link_status is up

  • Monitor the Primary Link Health Status CloudWatch metric (value of 1 means data is in sync)

  • Verify low client output buffer by running CLIENT LIST on your source Redis instances

Downtime: Near zero. Only the brief moment during the DNS/endpoint switch in your application.

Important: During migration, the ElastiCache cluster is read-only. You can use ElastiCache nodes for reads, but you cannot write to the ElastiCache cluster. All writes must continue going to the source Redis until complete-migration is executed.

Requirements:

Target requirements:

  • Target must NOT have encryption in-transit enabled (TLS must be disabled during migration; you can enable it after migration completes) (verify against current online migration prerequisites documentation)

  • Target must have Multi-AZ enabled (--automatic-failover-enabled)

  • Target must be using Valkey, or Redis OSS 5.0.6 or higher

  • Target must NOT be part of a global datastore

  • Target must have data tiering disabled

  • Number of shards in source and target must match (prerequisite).

  • Number of logical databases must be the same on source and target (set via databases in Redis config)

  • Target must have sufficient memory available to fit the data from the source cluster. See sizing-assessment.md for memory sizing guidance.

Source requirements:

  • Source Redis must be accessible from the ElastiCache VPC (security groups, VPC peering, VPN, or Direct Connect)

  • The security group attached to source Redis instances must allow inbound traffic from ElastiCache nodes

  • Source must NOT have AUTH enabled

  • Source protected-mode must be set to no

  • If source has bind configuration, it must be updated to allow requests from ElastiCache nodes

  • Data-modification commands must not be renamed (e.g., sync, psync, info, config, command, cluster)

  • All source Redis instances must be running on the same port

  • Source must have enough capacity to handle replication overhead

  • For cluster-mode disabled, source can be Redis 2.8.21 onward (via CLI). For cluster-mode enabled, source can be any cluster-mode enabled version.

Approach 3: Dual-Write (Application-Level)

Best for: Complex migrations, need full control, source not directly reachable from VPC, or need to transform data during migration.

Warning: Do NOT use DUMP/RESTORE for cross-engine migration (e.g., Redis OSS to Valkey). The serialization format is engine-specific and may fail silently or produce corrupted data. Use application-level copy or the ElastiCache migration tools instead.

Steps:

# Dual-write wrapper example
import valkey

old_client = valkey.Valkey(host="old-redis-host", port=6379, decode_responses=True)
new_client = valkey.Valkey(
    host="new-cache.serverless.use1.cache.amazonaws.com",
    port=6379,
    ssl=True,
    decode_responses=True,
)

# Feature flag to control read source
READ_FROM_NEW = False  # Flip to True when new cache is warm


def cache_set(key: str, value: str, ttl: int = 300):
    """Write to both caches during migration."""
    old_client.setex(key, ttl, value)
    try:
        new_client.setex(key, ttl, value)
    except Exception:
        # Log but don't fail -- old cache is still the primary
        pass


def cache_get(key: str) -> str | None:
    """Read from the active cache."""
    if READ_FROM_NEW:
        result = new_client.get(key)
        if result is None:
            # Fall back to old cache during warm-up
            result = old_client.get(key)
            if result is not None:
                # Backfill into new cache
                ttl = old_client.ttl(key)
                if ttl and ttl > 0:
                    new_client.setex(key, ttl, result)
        return result
    else:
        return old_client.get(key)

Downtime: Zero, if the application handles the dual-write correctly.

Trade-offs:

  • Requires application code changes

  • Double write latency during the migration period

  • Must handle failures on either cache gracefully

  • Most flexible: works even when source is not directly reachable from the VPC

Cutover Checklist

Complete each item before and during the cutover:

  • [ ] Target cache provisioned and accessible from application VPC

  • [ ] Data migrated or replication caught up (lag below acceptable threshold)

  • [ ] Application updated with the new ElastiCache endpoint

  • [ ] Authentication configured (RBAC or IAM on the target; serverless does not support AUTH tokens)

  • [ ] TLS enabled on the target (mandatory for serverless; strongly recommended for node-based)

  • [ ] Client connection code uses ssl=True / tls: {} for the new endpoint

  • [ ] Monitoring configured on the target (CloudWatch metrics, alarms, dashboards -- see monitoring sub-skill)

  • [ ] Security audit passed on the new cache (python3 scripts/security_audit.py --serverless <name> or --replication-group <name>)

  • [ ] Rollback plan documented (keep old source running until validation period ends)

  • [ ] DNS or application config switch executed

  • [ ] Smoke tests passed (read/write operations, latency within expected range)

  • [ ] Old source decommissioned after validation period (recommended: keep source running for 48-72 hours post-cutover)

Choosing an Approach

FactorSnapshot-BasedReplication-BasedDual-Write
DowntimeMinutes to hoursNear zeroZero
ComplexityLowMediumHigh
Network requirementS3 upload onlySource reachable from VPCNo direct connectivity needed
Data transformationNone (exact copy)None (exact copy)Possible during write
Data size limitPractical limit ~100 GBNo practical limitNo practical limit
Application changesEndpoint update onlyEndpoint update onlyDual-write logic required
Best forSmall data, simple setupLarge data, minimal downtimeComplex scenarios, unreachable source

Post-Migration Validation

After cutover, verify the migration was successful:

  1. Key count: Compare DBSIZE on source vs target

  2. Spot-check data: Read a sample of keys and verify values match

  3. Latency: Confirm read/write latency meets expectations (sub-ms for node-based, single-digit ms for serverless)

  4. Hit rate: Monitor cache hit rate -- expect it to ramp up over the warm-up period

  5. Error rate: Monitor application logs for connection errors or unexpected responses

  6. Run security audit:

    python3 scripts/security_audit.py --serverless <name>
# or
python3 scripts/security_audit.py --replication-group <name>

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.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

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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