AWS Database Services
AWS Database SRE Services
AWS database services comprise managed relational, NoSQL, in-memory, and analytics engines including Aurora, RDS, DynamoDB, and ElastiCache. JusDB delivers AWS database reliability engineering, custom parameter group tuning, Graviton cost optimization, and low-downtime migrations under your service agreement. Coverage hours and response targets are defined in the agreement; AWS's own service SLAs cover the underlying infrastructure.
Expert management, optimization, and agreed support for AWS managed database services. From Aurora and RDS to DynamoDB and Redshift — we help you run databases at scale with confidence.
Initial-response targets, not resolution guarantees. The target for your engagement is set in your service agreement.
AWS Database Categories
We provide expert SRE services across all AWS database categories, helping you choose and optimize the right database for your workload.
Relational Databases
ACID-compliant SQL databases for transactional workloads
NoSQL Databases
Flexible schema databases for modern applications
In-Memory Databases
Ultra-low latency caching and data stores
Analytics & Specialized
Purpose-built databases for specific use cases
AWS Databases We Support
Click on any database to learn more about our specialized SRE services, best practices, and how we can help optimize your deployment.
Amazon Aurora
MySQL & PostgreSQL compatible relational database; AWS cites up to 5x the throughput of standard MySQL.
Learn moreAmazon RDS
Managed relational database service for MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server.
Learn moreAmazon DynamoDB
Serverless key-value database with single-digit millisecond performance at any scale.
Learn moreAmazon ElastiCache
In-memory caching service supporting Redis and Memcached for microsecond latency.
Learn moreAmazon DocumentDB
MongoDB-compatible document database for JSON workloads at scale.
Learn moreAmazon Keyspaces
Apache Cassandra-compatible wide-column database for high-scale applications.
Learn moreAmazon Neptune
Graph database for highly connected datasets with billions of relationships.
Learn moreAmazon Timestream
Time-series database for IoT and operational applications at scale.
Learn moreAmazon MemoryDB
Redis-compatible durable in-memory database for ultra-fast performance.
Learn moreAmazon Redshift
Cloud data warehouse for analytics and business intelligence at petabyte scale.
Learn moreAmazon OpenSearch
Elasticsearch-compatible search and log analytics service for real-time insights.
Learn moreOur AWS Database SRE Services
Comprehensive database reliability engineering services to keep your AWS databases running smoothly, securely, and cost-effectively.
SRE Support & On-Call
Monitoring, incident response, and expert support for AWS database services. Business-hours coverage is Mon–Fri 09:00–18:00 IST (UTC+5:30); 24x7 on-call is available under your service agreement.
Performance Optimization
Query tuning, index optimization, and configuration adjustments for peak database performance.
Cost Optimization
Lower AWS database costs through right-sizing, reserved instances, and architecture optimization, measured against a pre-change baseline.
Security & Compliance
Encryption, IAM policies, security reviews, and preparing your AWS environment for SOC 2, HIPAA, and PCI DSS assessments.
Migration Services
Seamless migration to, from, or between AWS databases with zero downtime strategies.
Infrastructure as Code
Terraform, CloudFormation, and CDK automation for reproducible database deployments.
AWS Database Internals: Critical Failure Modes
AWS managed databases introduce subtle operational failure modes at cloud scale. Here are 3 critical edge cases our AWS DBRE team works to prevent:
Aurora Storage I/O Contention & Buffer Pool Thrashing
High-throughput OLTP transactions on Amazon Aurora exhaust instance local memory caches, forcing queries to repeatedly read 4KB pages from the distributed Aurora storage tier. Aurora storage latency and billable I/O operations skyrocket, causing catastrophic application latency spikes.
Transitioning instances to Aurora I/O-Optimized storage pricing, right-sizing instance classes to fit active working sets in RAM, and tuning innodb_read_io_threads and buffer pool instances.
DynamoDB Partition Key Hotspotting & WCU Throttling
Monotonically increasing or low-cardinality partition keys direct disproportionate write traffic to a single DynamoDB partition, exceeding the hard limit of 1,000 WCU or 3,000 RCU per physical partition and triggering ProvisionedThroughputExceededException errors.
Designing compound synthetic partition keys with random hash suffix salting, implementing DAX caching for read spikes, and configuring automated error retry logic with exponential backoff.
RDS Multi-AZ Failover DNS Propagation Latency
When RDS initiates an automated Multi-AZ failover, the primary DNS endpoint flips to the standby replica. Client application pools that cache DNS resolutions ignore the TTL, causing application threads to bombard the dead primary and incurring 5–15 minutes of downtime.
Deploying Amazon RDS Proxy for connection multiplexing and faster failover, configuring JVM/client networkaddress.cache.ttl to 1 second, and enabling TCP keepalive probes.
Our AWS SREs execute read-only CLI commands to audit Aurora replica lag and DynamoDB throttling thresholds without service interruption:
# Check Aurora replica lag and status across reader instances
aws rds describe-db-instances \
--filters "Name=db-cluster-id,Values=production-aurora-cluster" \
--query "DBInstances[*].{Instance:DBInstanceIdentifier,Role:DBInstanceClass,Status:DBInstanceStatus}" \
--output table# Inspect ThrottledRequests across DynamoDB table partitions aws cloudwatch get-metric-statistics \ --namespace "AWS/DynamoDB" \ --metric-name "ThrottledRequests" \ --dimensions Name=TableName,Value=production-table \ --start-time $(date -u -v-1H +%Y-%m-%dT%H:%M:%SZ) \ --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \ --period 300 --statistics Sum
How JusDB AWS Services compare to alternative options.
Operating databases on AWS requires continuous optimization of instance sizing, I/O storage tiers, and parameter groups. Here is how JusDB compares to AWS Enterprise Support, generic MSPs, and internal teams.
| Engineering Dimension | JusDB AWS SRE | AWS Enterprise Support | Generic MSPs | In-House Devs |
|---|---|---|---|---|
| Aurora & RDS Parameter Group Hardening | Custom parameter group calibration (max_connections, innodb_buffer_pool_size, autovacuum_vacuum_cost_limit, pg_stat_statements) tuned to workload metrics | Provides default parameter groups; AWS Support provides documentation links rather than tuning database engine flags | Uses default AWS parameter groups without adjusting memory allocations, lock timeouts, or connection parameters | Unmodified RDS defaults leading to connection exhaustion spikes and autovacuum falling behind during peak loads |
| DynamoDB Modeling & Partition Hotspot Prevention | Single-table design architecture, synthetic partition key salting, GSI sparse indexing, and dynamic auto-scaling policies | CloudWatch metrics report ProvisionedThroughputExceededException; customer is left to restructure partition keys | Treats DynamoDB like a relational table; sets arbitrary provisioned capacity units resulting in high throttle rates | Hot partition keys saturate 1,000 WCU per partition limit, causing cascading application timeouts and elevated costs |
| AWS Database FinOps & Cost Reduction | Graviton3 upgrades, Aurora I/O-optimized vs standard analysis, idle replica cleanup, and Savings Plans/RI modeling, with savings measured against a pre-change baseline | AWS Compute Optimizer flags basic idle resources; suggests larger instance upgrades during CPU spikes instead of query tuning | Reviews monthly AWS bill but lacks database engine depth to identify wasted provisioned IOPS or unindexed table scans | Unmonitored EBS storage autoscaling and provisioned IOPS (io2) driving unpredicted monthly cloud budget overruns |
| Response Coverage & Named DBRE War Room | Agreed initial-response targets (24x7 on-call available) with direct war room access to senior Database Reliability Engineers | Multi-tiered AWS Support; requires costly Enterprise Support tier with automated case routing and generic cloud engineers | Offshore ticket dispatcher operating from basic restart runbooks without deep Aurora storage or replication knowledge | DevOps engineers paged at night for mysterious Aurora failovers without specialized database diagnostic tooling |
| Cross-Region Disaster Recovery & Global Tables | Aurora Global Database with storage-level replication (<1s cross-region lag) and DynamoDB Global Tables tested with drills | Global Database deployment available via console; customer must design and execute complex regional failback procedures | Unfamiliar with Aurora storage replication architecture; relies on slow cross-region automated snapshot copying | Untested disaster recovery failover procedures that fail under regional outages due to IAM or VPC peering misconfigurations |
| Zero-Downtime AWS Database Migrations | AWS DMS CDC replication, Blue/Green deployments, and short, rehearsed cutovers with pre-validated fallback pathways | Provides AWS DMS tool, but customer must configure ongoing task replication, LOB handling, and table mappings | Requires multi-hour maintenance windows using mysqldump or pg_dump, causing extensive application downtime | Stalled DMS replication tasks due to memory exhaustion or binary log truncation on high-throughput source databases |
Why Choose JusDB for AWS Databases?
AWS Database Migration Services
Whether you're migrating to AWS, between AWS services, or away from AWS to reduce vendor lock-in — our experts plan each cutover to minimise downtime, with a tested rollback path.
Migrate TO AWS
On-premise MySQL/PostgreSQL to Aurora, MongoDB to DocumentDB, Cassandra to Keyspaces
Migrate BETWEEN AWS
RDS to Aurora, DynamoDB to DocumentDB, ElastiCache to MemoryDB
Migrate FROM AWS
DynamoDB to Cassandra/Aerospike/ScyllaDB, Aurora to self-managed PostgreSQL
Common questions about AWS database management & SRE
Direct technical answers from our Principal AWS Database Reliability Engineers.
Which AWS database engines does JusDB support?
We support the entire AWS database portfolio: Amazon Aurora (MySQL & PostgreSQL), Amazon RDS (PostgreSQL, MySQL, MariaDB, Oracle, SQL Server), DynamoDB, ElastiCache (Redis/Memcached), MemoryDB, DocumentDB, Keyspaces, Neptune, Timestream, Redshift, and OpenSearch Service.
How do you reduce costs on AWS databases?
We move suitable instances to Graviton3/Graviton4 processors, right-size over-provisioned EBS and Aurora storage tiers, convert eligible workloads to Aurora I/O-Optimized, clean up forgotten dev/test snapshots and idle read replicas, and structure Reserved Instance / Savings Plans coverage. Results depend on the workload; we baseline before and measure after each approved change.
How does JusDB handle an AWS database production incident?
Alerts route to the Database Reliability Engineers assigned to your account, who join your Slack or Teams incident bridge. We execute non-blocking diagnostics to isolate lock contention, memory leaks, and I/O bottlenecks without waiting on AWS Support queues. Response commitments are agreed. Initial-response targets are 2 to 4 hours during covered business hours, Mon–Fri 09:00–18:00 IST (UTC+5:30). Where your service agreement includes 24x7 on-call, the initial-response target for P1 incidents is 30 minutes. Targets are not resolution guarantees.
Can you help migrate our workloads off DynamoDB or Aurora to reduce lock-in?
Yes. We specialize in zero-downtime migrations from DynamoDB to open-source alternatives like Cassandra, ScyllaDB, Aerospike, or MongoDB, and from Amazon Aurora to self-managed or Kubernetes-native PostgreSQL using CDC pipelines.
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