Elastic Cloud
Elastic, without running the cluster — Elastic Cloud is the managed platform: Hosted across 50+ regions on resource-based pricing, or Serverless on consumption with nothing to size.
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Same software. Better outcome — at a lower cost.
How it’s rated
Full scoreboard ↓Data residency & processing — answered by deployment
Self-managed
Stored AND processed by you
Runs on your own infrastructure, including fully air-gapped. Both questions answered by definition — the data never leaves.
Elastic Cloud
50+ regions — confirm both
If you choose managed, confirm storage AND processing location for your region in writing, as you would with any SaaS.
Elastic Cloud Hosted lists three Indian regions — AWS Mumbai, Google Cloud Mumbai and Azure Central India (Pune) — so you choose where the deployment’s data is stored. Processing location is a separate question: get it in writing. Where a mandate rules out any vendor-operated service, self-managed Elastic is the same software under your control.
Quick answer
The Elastic platform family
This page covers Elastic Cloud — the managed way to run all of them. The other Elastic products:
Quick facts
30-second orientation- Product
- Elastic Cloud — the managed Elastic Stack
- What it is
- The same software, with the operations moved to Elastic
- Vendor
- Elastic N.V. — CEO Ash Kulkarni
- Runs on
- AWS · Azure · Google Cloud
- India regions
- Mumbai (AWS) · Central India (Azure) · Mumbai (GCP)
- Priced on
- Consumption — compute and storage actually used
- Tiers
- Standard · Gold · Platinum · Enterprise
- Serverless
- Usage-based; no nodes to provision
- Data residency
- Yours to choose — Indian regions available
- Data processing
- Not documented per region — confirm in writing
- The honest limit
- No air gap — that requires the self-managed path
- Free tier
- Elasticsearch is AGPL open source; self-managed Basic is free
- Alternative
- Self-managed Elastic — same software, you operate it
- Buy in India via
- TechBag — INR invoicing, GST, tier sizing
Understand managed vs self-managed before you buy it
Most product pages skip this. We start here — so you buy a capability, not a buzzword.
What is it?
The Elastic Stack, run for you — Elasticsearch, Kibana and the Search, Observability and Security solutions on AWS, Azure or Google Cloud, with Elastic handling the cluster.
Running Elastic yourself vs Elastic Cloud — the honest table
What moving to managed actually changes, dimension by dimension.
| Dimension | Self-managed Elastic | Elastic Cloud |
|---|---|---|
| Cluster operations | Your team: sizing, shards, failed nodes | Elastic runs them |
| Version upgrades | Planned, tested and often deferred | Handled; Kibana kept in step |
| Snapshots & HA | A regime you design and test | Managed across zones |
| Time to a cluster | Hardware or cloud build first | Minutes from the console |
| India residency | Wherever you put it | Mumbai (AWS, GCP) or Central India (Azure) |
| Air gap | Fully possible | Not possible — Elastic operates it |
| Licence | Free Basic under AGPL; paid tiers | One bill: resources plus tier |
| Best fit | Air-gap mandates; spare platform team | No spare ops capacity; India region needed |
Same software on both sides — the difference is who carries the operations, and whether an air gap is on the table.
The six pieces of the platform
Vendors love diagrams; buyers need to know what they’re actually operating. Here’s the whole platform, demystified.
Elasticsearch
Elasticsearch is the distributed engine under everything Elastic sells; on Elastic Cloud you size nodes, tiers and storage rather than build them.
Kibana
Kibana dashboards, search, alerting and the Observability and Security workspaces are managed and upgraded in step with the cluster.
Solutions
One deployment can carry search, observability and security, so one store and agent replace separate log, SIEM and APM tools.
Tiers
Standard covers core search; Gold and Platinum add alerting, ML anomaly detection and replication; Enterprise adds advanced Security.
Regions
Runs on AWS, Azure and Google Cloud, including Mumbai on AWS and GCP and Central India on Azure; confirm the region for your service.
Serverless
Serverless projects remove capacity planning and bill on usage, suiting spiky loads; model both options rather than assuming it is cheaper.
The same Elasticsearch and Kibana you could run yourself — Elastic operates the cluster, and you choose the cloud, the region and the tier.
Seven capabilities. Provision, scale, operate.
What Elastic Cloud takes off your hands, and what it adds on top of the software you could run yourself — the operational pieces that decide whether managed is worth it.
A cluster in minutes
Deploy a sized, production-ready Elastic Stack on AWS, Azure or Google Cloud without procuring hardware or building a cluster.
Scale without a rebuild
Add nodes, storage or hot-warm tiers as data grows, rather than re-architecting a cluster you sized eighteen months ago.
Indian data residency
Deploy into Mumbai or Central India so an India-residency obligation is answered by where you put the cluster.
Version upgrades handled
Elastic runs the upgrade path and keeps Elasticsearch and Kibana in version alignment — the tedious part of self-managing.
Replication and snapshots
Managed high availability across zones, with automated snapshots, rather than a backup regime you design and test yourself.
Search, Observability and Security
License any combination on one deployment, so logs collected once serve operational monitoring and threat detection without a second copy.
Machine-learning anomaly detection
Unsupervised anomaly detection on the higher tiers — genuinely useful, and genuinely not included at Standard.
Watch what runs on Elastic Cloud
Serverless scaling, and one of the solutions you can license on a deployment — from Elastic’s own channels.
Scaling Up Elastic Cloud Serverless
How a serverless project scales up with no nodes to size.
Elastic Security Solutions Overview
One of the solutions you can license on an Elastic Cloud deployment.
Want a live, India-context walkthrough for your environment?
Book a guided demo →Same software. Someone else runs the cluster.
Why teams move to Elastic Cloud — and the three limits that should send you to self-managed instead.
The decision is who operates the cluster, not what the software does
Elastic Cloud is not a better Elastic: it is the same Elasticsearch, Kibana and solutions with the operations moved to Elastic. The real question is whether your team should run a distributed search cluster — sizing, shards, upgrades, 2am node failures. Teams that already do it well can self-manage for less licence cost.
Indian regions, documented in writing
Elastic Cloud deploys into Mumbai on AWS and Google Cloud, or Central India on Azure. For an IRDAI-regulated insurer or a bank under RBI localisation expectations, a missing India region on a cloud-only rival is a disqualification, so choosing and evidencing where the cluster sits is a structural advantage.
One deployment, several jobs, no second copy of your data
Most organisations run a log platform for operations and a separate SIEM for security, collecting, storing and paying for the same data twice. On Elastic Cloud one deployment carries Observability and Security on the same indices. If you already run Elastic for logs, adding Security is a licence decision.
Consumption pricing behaves differently from an ingestion meter
Elastic Cloud bills for the compute and storage you consume, not per gigabyte ingested. Noisy sources still cost you, but you can tier data to cheaper storage, set retention per index and size the cluster to your pattern — cost you engineer, rather than one a per-GB licence dictates.
The honest limits
Three limits. No air gap, since Elastic operates it — use self-managed Elastic instead. Machine-learning anomaly detection and cross-cluster replication aren’t in Standard, so read the tier table before costing. And spiky ingestion means a spiky bill; set retention and tiering policy at the start.
The numbers behind the platform
What your Elastic Cloud rollout looks like
Decide managed or self-managed first
If you must run air-gapped, self-manage Elastic; otherwise weigh spare platform-engineering capacity against the subscription.
Choose the region deliberately
If Indian residency binds you, pick Mumbai on AWS or Google Cloud, or Central India on Azure, and record why for the auditor.
Size the tier against the capability you need
Map needed features to tiers, ML anomaly detection especially; sizing on Standard then finding it at Platinum is the commonest error.
Model retention and tiering before you load data
Set hot, warm and delete policies per index on day one; consumption pricing rewards it, and retrofitting after a year is far harder.
Review the bill against the pattern
Make someone own the monthly consumption review, because a source that doubles in volume goes unnoticed until it shows up as cost.
The review scoreboard
Modelled on Gartner Peer Insights structure. *Counts and breakdowns are illustrative pending verified review collection.
Quick poll — what’s driving your evaluation?
Talk to an advisor“We moved off a self-managed cluster after our one Elasticsearch expert resigned. That risk was the entire business case.”
“Mumbai region meant our residency question had a one-line answer. Two other vendors on the shortlist could not say the same.”
“Read the tier table properly. We sized on Standard and then discovered machine learning was two tiers up.”
“Consumption pricing is fair but it is not set-and-forget. Retention and tiering policy needs an owner or the bill drifts.”
Where everyone sits — the grids
Analyst firms bury this view behind paywalls, and review-site grids score satisfaction, not fit for your estate. So here’s TechBag’s synthesis of the ways to run Elastic, and the managed alternatives — tap any vendor to see why it sits where it does.
TechBag Elastic Deployment Grid
How much operational work each option removes vs how much control it leaves you.
Elastic runs the cluster; you still choose cloud, region and tier — no air gap.
Operations Removed × Residency Answer
Managed platforms compared on how much work they remove vs how directly they answer an India-residency question.
Operations removed; three documented Indian regions.
Positions are TechBag’s illustrative synthesis of public review-platform data and vendor documentation — not a reproduction of any analyst graphic. Verify before relying on it.
Elastic Cloud vs the field
The four ways to run Elastic, side by side. The software is identical in every column — what changes is who operates it, where it can sit, and how the bill behaves.
| Dimension | Elastic Cloud | Self-managed Elastic | Elastic on your own cloud account | Elastic Serverless |
|---|---|---|---|---|
| Who operates the cluster | Elastic — sizing, upgrades, availability | You, entirely | You, on infrastructure you rent | Elastic, with no nodes to size at all |
| Licence cost | Consumption — compute and storage used | Basic tier is genuinely free (AGPL) | Subscription if you want commercial features | Usage-based, no provisioned capacity |
| True cost to compare | One bill: infrastructure AND operations | Infrastructure plus real engineering time | Cloud bill plus your engineering time | One bill, scales with what you do |
| Air-gapped deployment | Impossible — Elastic runs the control plane | Fully supported | Possible in a private/isolated network | Impossible by design |
| India data residency | Mumbai (AWS/GCP), Central India (Azure) | Wherever you put it — yours to prove | Your account, your region choice | Check region availability for serverless |
| Version upgrades | Handled, and kept in version alignment | Yours — the task teams most often defer | Yours | Invisible to you |
| Key-person risk | Low — the vendor holds the expertise | High — often exactly one person knows it | High, same reason | Lowest |
| Cost predictability | Responsive to load — needs a retention policy | Fixed infrastructure, fixed salary | Depends on your commitments | Most variable — spiky load, spiky bill |
| Best fit | No spare platform capacity; India region needed | Air-gap mandates, or real spare capacity at scale | Large committed cloud spend you already hold | Spiky or unknown load you cannot size |
Does Elastic Cloud fit you?
Honest fit signals — because the fastest way to lose your trust is to pretend one product wins every scenario.
Choose Elastic Cloud if…
- ✓You want the Elastic Stack without running a distributed search cluster yourself
- ✓You need an Indian region — Mumbai or Central India — and can evidence that choice to an auditor
- ✓Your Elasticsearch expertise sits with one or two people and that dependency worries you
- ✓You would rather engineer cost through retention and tiering than negotiate a per-GB licence
Choose self-managed Elastic instead if…
- ✓A regulator, a contract or an air gap rules out a vendor-operated control plane
- ✓You already run Elasticsearch competently and have genuine spare capacity — the Basic tier is free
- ✓You are at large, steady volumes where engineering cost grows more slowly than consumption
Run it in your own cloud account if…
- ✓You hold a substantial committed-spend agreement with AWS, Azure or GCP
- ✓You need full control of networking and data placement
- ✓You accept that you still supply all of the operations
Look at Wazuh or Splunk instead if…
- ✓You want a security platform complete out of the box rather than a stack to assemble (Wazuh)
- ✓You have a detection-engineering function that wants the deepest query language (Splunk)
Elastic Cloud is the managed way to run the stack behind 20 SIEM & log management products TechBag carries. The SIEM & Log Management guide narrows them to a shortlist and shows the reasoning. →
Self-managed, or managed?
Elastic Cloud Hosted bills on the resources you provision plus the tier — so the question that decides your bill is whether running the cluster yourself costs less than letting Elastic run it. The engine is free under AGPL; what is not free is your engineers’ time on shard strategy, index lifecycle, capacity and upgrades. Drag both sliders. Illustrative, at ₹12,000 per fully-loaded engineer-day and ~₹84/USD.
Engineer-days means real time on shard strategy, index lifecycle, capacity planning and version upgrades — not incident response. If you put 0, you are assuming the cluster runs itself, which is the assumption this calculator exists to question. Illustrative: your TechBag quote models your real tier and resources.
Three ways to consume it
Elastic Cloud Hosted is priced on provisioned resources plus a tier (Standard, Gold, Platinum, Enterprise); Serverless is priced on usage — GB ingested and retained for Observability and Security, compute units for Search. Self-managed is shown for comparison: the engine is free under AGPL and you supply the operations. Figures are Elastic’s listed “as low as” entry rates and scale with what you use. TechBag scopes tier and deployment and quotes in INR with GST.
Self-managed
Best for on-prem and air-gapped
- Engine free and open source — pay for a tier above it
- Runs fully air-gapped; residency answered by definition
- You operate the cluster — price your engineers’ time
Elastic Cloud Hosted
Best if you want it managed
- Listed from $99/mo Standard to $184/mo Enterprise at entry size
- Priced on provisioned resources, not per seat or per GB
- 50+ regions; support charged as a % of consumption above Standard
Serverless
Best for variable volume
- Observability from $0.07/GB and Security from $0.09/GB ingested, plus retention per GB/month
- Search projects bill on compute units (VCUs) per hour plus storage
- No nodes to size — pure consumption, least predictable under spiky load
Buy it for less — TechBag pricing beats list
Whatever the list prices above, TechBag negotiates a significantly better deal — with GST-compliant INR invoicing and local support. Ask us for your discounted quote.
Get an India-ready quote
Tell us your requirements and current tools — we’ll model it against what you spend today.
The 8 questions to ask before choosing managed Elastic
Take this into your next vendor call — including ours.
Does any mandate require air-gapped or on-premises operation? If so, Elastic Cloud is out — use self-managed.
Do we have genuine spare platform-engineering capacity to run a distributed cluster, counted honestly?
Which region will hold the deployment, and does that satisfy our residency obligation in writing?
Which tier contains the capabilities we actually intend to use — machine learning especially?
Are we licensing Search, Observability, Security or a combination, and on the same deployment?
What is our per-index retention and tiering policy, decided before we load data rather than after?
Do we already run Elasticsearch for logs, making Security a licence decision rather than a new platform?
Who owns the monthly consumption review, so a source that doubled in volume gets noticed?
Questions buyers ask
Ready to evaluate Elastic Cloud?
Decide managed or self-managed, pick the region deliberately, and size the tier against the capabilities you will actually use — quoted in INR with GST.
Stats, ratings, review counts and pricing are illustrative and sourced from public materials; verify before purchase.