20 articles on playbook — what drives the cost, how it is priced, and where the savings actually are.
A 30 percent AWS reduction is achievable on most untouched accounts, and the order of the levers matters more than the list. Delete first, resize second, commit last. Here is the sequenced playbook with expected savings per step.
Azure reductions come from a different shape of waste than AWS: premium disks, orphaned NICs and public IPs, oversized VMs, and Log Analytics ingestion. Here is the ordered playbook with real meter prices and expected savings.
GCP has its own waste profile: idle persistent disks, unattached external IPs, snapshot sprawl, oversized machine types, and BigQuery scans. Here is the sequenced playbook with real rates and expected savings per lever.
A cost program that starts with a tool selection stalls. One that starts with a baseline, a hit list, and a weekly number delivers in the first month. Here is a day by day plan for the first 30 days with expected outcomes.
Non-production is typically 30 to 40 percent of a cloud bill and used for 30 percent of the hours. The savings are large and safe, but only if the changes do not add friction. Here is the playbook that cuts spend without cutting velocity.
A week has 168 hours and most non-production workloads need about 45. Turning things off for the rest is the highest ratio saving in cloud. Here is the arithmetic, the implementation, and the resources that keep billing anyway.
Zombie resources are alive on the invoice and dead in production: disks with no instance, clusters with no pods, gateways with no traffic. Here is the hunt playbook, the detection query for each type, and how to delete safely.
Storage rarely spikes, it creeps, which is why it is the least audited line on most bills. Here is a five step cleanup covering tier policy, incomplete uploads, versioning, replication, and block storage, with real per GB rates.
Backups are the one cost line with no natural ceiling: a daily schedule with no expiry runs forever. Here is how to audit snapshot spend, set retention that satisfies compliance, and cut 50 to 80 percent without losing recoverability.
Right-sizing stalls when it becomes a permanent backlog. Running it as a time boxed sprint with a ranked list, a batch cadence, and a rollback rule ships 30 to 60 resources in two weeks. Here is the sprint plan.
ARM based instances price 10 to 20 percent below their x86 equivalents and often deliver better price performance than the headline rate suggests. Here is the staged migration playbook, the workloads that port cleanly, and the ones that do not.
A commitment is the only cost lever you cannot undo. Buy it at the wrong time or the wrong size and you have converted fixable waste into a three year obligation. Here is the sizing method, the timing rule, and the coverage targets.
Data transfer is billed per GB with no resource to point at, which is why it is the hardest line to attribute and the easiest to ignore. Here is how to find the flows, rank them, and cut them, with the per GB rates that matter.
Observability spend grows with traffic, with services, and with every new dashboard, and it is often the second largest line after compute. Here is how to cut it 40 to 70 percent while keeping the signal you actually use.
Every cluster carries a fixed overhead before a single pod runs: control plane, system nodes, load balancers, and monitoring agents. Running eight clusters at 15 percent utilisation is expensive in a specific, measurable way.
A load balancer with no targets and a public IP with no association each cost a few dollars to tens of dollars a month. Individually trivial, collectively thousands. Here is how to find them, verify they are dead, and remove them safely.
Autoscaling is sold as a cost control and often operates as a cost floor. Minimum counts set for comfort, thresholds that never trigger, and cooldowns that hold capacity long after demand fell all quietly set a bill you never chose.
Third party software bought through a cloud marketplace lands on the same invoice as compute but obeys different rules. It is rarely audited, often over-licensed, and frequently the largest line nobody in engineering owns.
Due diligence looks at gross margin, unit economics, and whether infrastructure spend scales with revenue. A cost cleanup before the process starts changes the numbers investors see. Here is what to fix and in what order.
When spend triples overnight, the priority is stopping the burn, not understanding it. Here is an hour by hour runbook: contain first, diagnose second, then decide what to reverse and what to keep.