When it comes to seamlessly scaling your applications, a top-notch engineering team will be your foundation. Next comes the decisions to build or buy your infrastructure, DNS, monitoring, and analytics tools. Julian Lemoine, Co-Founder, and CTO of Algolia will share his lessons learned on how to stay focused and innovative as you scale while also avoiding the innovation for innovation’s sake pitfalls.

1. Founder’s Guide to
Scaling Applications
When to Build, When to Buy…and What Breaks
Julien Lemoine - Co-founder & CTO @Algolia
@jlemoine_algo

2. Algolia in a few numbers
Team
● 300+ people in 6 offices
● 100+ software engineers
Infrastructure
● 2000+ bare metal machines in 70+ data centers
● 200TB+ of RAM, 2PB+ of SSD
● 10 Gbps average bandwidth usage worldwide
Usage
● 7000+ customers
● 200B+ API calls per month

3. We have a very strong team!
Like all companies, we need to stay
focused and innovate to conquer the
market!

4. Top-notch engineering team
Pros
● Key to the success of the company
● They love challenges and solving problems
● And they solve problems super quickly!
Cons
● They always find a lot of reasons to build not buy. Wouldn't it be the
famous "not invented here" or "reinventing the wheel" syndrome?
● Often under-evaluate or do not see the long-term cost

5. Build vs. Buy
Decision #1: Infrastructure

6. Infrastructure choice
Build vs. Buy: Cloud or bare-metal infrastructure
When: Q1-2013 (before launching the product)
Risk: A lot more to develop (High Availability in software)

7. Infrastructure choice
Build or Buy: Cloud or bare-metal infra
When: Q1-2013 (before launching the product)
Risk: A lot more to develop (High Availability in software)
Decision: bare metal because of performance
Conclusion: We were very lucky! It was a big risk but became
key for our success and lead to two big innovations in our
product.

8. Build vs. Buy
Decision #2: Geo aware DNS

9. Geo-aware DNS choice
Build or Buy: Find a provider or build our own DNS
When: Q4-2014 (for our Distributed Search Network)
Risk: losing our focus, a lot of existing managed DNS

10. Geo-aware DNS choice
Build or Buy: Find a provider or build our own DNS
When: Q4-2014 (for our Distributed Search Network)
Risk: losing our focus, a lot of existing managed DNS
Decision: develop our own anycast-DNS
Conclusion: it was a mistake! We discovered a startup working
on a SaaS product few months late

11. Build vs. Buy
Decision #3: Monitoring

12. Monitoring choice
Build or Buy: too much limit with our existing provider. Find a new one
or build based on opensource
When: Q1-2016
Risk: Focus, cost of maintaining our solution

13. Monitoring choice
Build or Buy: too much limit with our existing provider. Find a new one
or build based on opensource
When: Q1-2016
Risk: Focus, cost of maintaining our solution
Decision: Build. The team built a working prototype quickly using OSS
Conclusion: Was again a mistake! We discovered a new API solution
a few months later!

14. Build vs. Buy
Decision #4: Analytics

15. Analytics choice
Build or Buy: We re-developed our system 3 times, each time asking
ourselves the build or buy question
When: Q3-2013, Q2-2014, Q4-2016
Risk: Focus, cost of maintaining our solution

16. Analytics choice
Build or Buy: We re-developed our system 3 times, each time asking
ourselves the build or buy question
When: Q3-2013, Q2-2014, Q4-2016
Risk: Focus, cost of maintaining our solution
Decision: Build, then Build, then Buy
Conclusion: It was very positive to iterate. The last Buy option actually
failed and we finished we a mix of build/buy by using several GCP
components

17. How to not reinvent the wheel?

18. How to not reinvent the wheel?
● Assume the initial choice is wrong
Team needs to be in a growth/adapt mindset
● Be careful about the bad reasons
Learning the tech or having ownership are never a good reasons (hint: think about turnover!)
● There are SaaS solution for most needs
If not today, it will come!
● More and more mix of Build & Buy
IaaS, hosted services and API in general
● Build for short term or if you have a factor 10
Whatever the factor 10 (cost, UX, performance, etc.)

19. Thank you