Elastic (ESTC) – My Thesis
(Not Advice)
Accumulate: On dips Target Exit: None — follow the product journey closely. Keep in portfolio as long as they continue to innovate.
Dated: 8-Oct-2025
Why I'm Writing This
This is not financial advice. It's a personal investment thesis — a way for me to stay honest with myself about why I hold Elastic. If others find value in this reasoning, great — but please do your own research.
Background: The Ones That Got Away
When I was preparing for a job interview out of engineering school in 2006, my dad — not a tech guy — sent me an article on cloud computing. He said, "This might come up — read it."
He had the financial acumen but no technical knowledge to invest in the cloud. I understood the technology, but had zero commercial acumen to see the investment opportunity. Had either of us bought Amazon back then, even a few thousand dollars would've compounded into a small fortune.
I forgive myself for missing Amazon. I was young and financially illiterate.
What I can't forgive myself for is what came later.
Years later, while heading IT contracts and commercials for a major Australian enterprise, I dealt with a BMC escalation — they were charging a penalty for Remedy license "overuse." It was obvious this wasn't about value or innovation — it was about squeezing the customer to meet their own growth targets.
What followed, right before my eyes, was ServiceNow eating BMC's entire market. One by one, enterprises switched over. The market had chosen innovation over inertia.
I watched it unfold, fully understanding the tech — but not investing a single dollar. ServiceNow's stock is up more than 35× since IPO.
I've forgiven myself for missing Amazon. I haven't forgiven myself for missing ServiceNow.
The Challenge: When Everyone Understands Recurring Revenue
The idea of recurring revenue + high gross margins = great business is no longer a secret. That playbook is priced in.
Today, most enterprise SaaS IPOs launch at 10–20× sales, leaving no room for "multibagger" upside.
A case in point: HashiCorp (Terraform). I implemented Terraform in a large enterprise — I knew its potential intimately. But when it IPO'd, the valuation made zero sense. Brilliant product, but no commercial margin of safety. Then came IBM, who bought them, hiked prices, and started milking customers — déjà vu from the BMC days.
So the challenge today isn't finding great technology — it's finding great technology that's still mispriced.
My Spidey Sense: Observability Pain Points
Over the past few years, my "spidey sense" has been tingling around Observability — monitoring, logging, and application performance tools.
Enterprises are frustrated. Costs have spiraled.
Platforms like Datadog and Dynatrace deliver great insights — but at unsustainable prices. Don't even get me started on log management via Splunk.
I've seen small companies literally go back to Python scripts rather than pay those ingestion-based invoices.
I've listened to Dynatrace earnings calls. They keep saying they'll enter SIEM (Security Information & Event Management) which should increase optionality — but it feels more like marketing than mission.
When vendors start focusing on price extraction rather than value creation, disruption is usually close behind.
The Trigger: A Telco Chooses Elastic
Recently, my mentor Jim mentioned that a large telco enterprise had selected Elastic as its observability platform — because Dynatrace was too expensive.
That one sentence caught my full attention.
Why Telcos Matter
Telcos are, in my opinion, the toughest IT customers in the world.
They earn about A$50 ARPU per month — but for that they must:
- Maintain massive network and tower infrastructure
- Manage entire IT stacks
- Provide critical 24/7 services (where downtime is national news)
Compare that to a bank: if IT goes down, it's inconvenient. If a telco goes down — it's an emergency.
And yet banks make billions per quarter; telcos scrape profits from low-margin revenue. That's why telco IT systems must deliver maximum resilience at minimal cost.
So if a telco is trusting Elastic for observability — that's a major vote of confidence in both cost efficiency and technical capability.
Falling in Love with Elastic
When I started digging, I discovered Elastic was no longer just a search company. It had evolved into a platform powering three major product lines:
Search
Enterprise-grade data search and analytics
Observability
Logs, metrics, and traces for system health
Security / SIEM
Threat detection and monitoring
That pivot impressed me deeply.
Elastic didn't abandon its core — it built on top of it. They took their world-class search engine and turned it into adjacent, high-value products.
That shows two things:
- Innovative culture — they can reinvent without losing identity. 1.
- Product integrity — their core technology actually works across domains. 2.
To me, that's the same DNA that made Amazon and ServiceNow great: a platform mindset, not a product mindset.
The AI Tailwind: Search Becomes Context
Elastic's original strength — search — has just found a second life in the AI era.
Every useful AI application needs context. Large Language Models (LLMs) can't just "read everything" — you must feed them relevant data through embeddings and vector databases.
That's where Elastic shines. It has become one of the most capable vector databases on the planet — allowing enterprises to connect private data with AI agents efficiently.
I know this firsthand.
When I began experimenting with AI coding, I built a small project where AI needed to interpret project data from emails and match it to a Postgres database. To do that, I needed embeddings and a vector database.
That was my "aha" moment — realizing that search and vectors are the backbone of enterprise AI.
So when I discovered that Nvidia had endorsed Elastic as its preferred vector database partner, it all clicked. Elastic isn't just surviving the AI wave — it's in the engine room.
Valuation View
Elastic currently trades around 5–6× sales — expensive by normal standards, but cheap in SaaS land where peers like Dynatrace (9×) and Snowflake (25×) sit.
Elastic Sales Multiple
Current valuation
Dynatrace
Peer comparison
Snowflake
Premium SaaS valuation
Gross Margins
SaaS standard
It's not GAAP-profitable yet but cashflow positive, which is what matters at this stage. Given SaaS gross margins (~75–80%), any meaningful revenue uplift drops fast to the bottom line.
So the question isn't whether Elastic is cheap — it's whether Elastic has optionality. And it does: Observability + SIEM + AI Infrastructure. Each of these could be a standalone billion-dollar segment.
Risks & Watchouts
# | Risk | Commentary |
1 | Valuation Compression | SaaS multiples have already rerated; further compression possible. |
2 | Tech Churn | Enterprise software cycles move fast — today's darling can be tomorrow's legacy. |
3 | Stock-Based Compensation | SBC >30% of revenue, a common but real dilution risk. |
4 | Open-Source Model | Great developer ecosystem, but competition from forks like AWS OpenSearch persists. |
5 | Amazon Factor | If Bezos decides to heavily subsidize OpenSearch, Elastic's moat could narrow quickly. |
Summary & Horizon
After missing ServiceNow, I've been searching for the next enterprise software story built on innovation, not financial engineering. I believe Elastic fits that mold.
It's cost-efficient, innovative, culturally strong, and now strategically positioned at the intersection of data + AI.
This isn't a one-year trade. It's a 10–15 year horizon — a bet on the enduring value of platforms that evolve with technology.
Reinvented itself across three growth vectors
Search, Observability, SIEM
Poised to power enterprise AI
Through vector search
Built on strong engineering roots
Developer loyalty
Cost advantage validated
Real-world enterprise wins (like Telco)
If the company keeps innovating and compounds modestly over the decade ahead, 5–10× returns don't feel unreasonable.
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If you would like to browse all my earlier investment theses, you can find them here: