The Dutch government relies on a complex mix of technologies to deliver digital services. This makes it difficult to monitor performance and identify issues when they arise. Capgemini implemented Elastic solutions to provide observability across the heterogeneous infrastructure. This allowed problems to be traced and resolved in minutes rather than days. The improved visibility has enhanced operational stability and reduced breakdowns. Capgemini sees continued growth in demand for Elastic technologies from both government and commercial customers.

1. OBSERVABILITY WITHIN
THE DUTCH GOVERNMENT
Marcus König
Managing Consultant, Capgemini
CSD Java Cluster

2. WHAT WILL THIS BE
ABOUT?
The digital landscape within Dutch government is a
complex and heterogeneous mix of technologies. To
keep the lights on in operation and allow for quick
turn-around times, Elastic is the dominant choice to
generate reliable insight.
During the following half-hour, we will take a look
behind the curtain of what solutions we deploy to
achieve this goal.

3. WHO IS THAT GUY ON
MY SCREEN?
• Marcus König, 42
• Managing Consultant
• Elastic Certified Engineer
• Working on Big Data / Analytics within the
CSD Java Cluster
• Around 25 years of experience in software
engineering

4. WHAT IS THAT COMPANY HE IS
TALKING ABOUT?
• A multinational corporation (France, Netherlands, Germany, England, USA,
India)
• Global leader in consulting, transformation, technology and engineering
services
• In the Netherlands: big footprint in government and adjacent sectors
(f.e. defense & police)
• Provides large scale integration on behalf of its customers
• Directly on location or via remote roles

5. MY ROLE INSIDE
THE CSD JAVA
DIVISION:
• Analysing customer data, scenarios and
implementations
• Designing and implementing prototype
solutions for identified problems
• Leading engineering teams during scale
up, deploy and maintenance

6. • The Netherlands run most of their government digitally. Many
services are available either additionally or primarily online
• Large digital integrators are busy constantly maintaining, extending
and updating this infrastructure
• As one of the biggest providers for custom software development in
Benelux, Capgemini is closely involved in this process
SO, WHAT WAS THE STORY WITH
THE DUTCH GOVERNMENT?

7. • Diverse mix of different deployments of technology (Java, Databases, old
legacy mainframes, new REST services)
• “Old meets new” 1990s or older mainframes against f.e. 2021 REST Java)
• Monolithic vs. API-centric
• Distributed in local server installations as well as partially in the cloud
• No single source of origin - 1st and 3rd party originated architectures on behalf
of the government
WHAT DOES THE
ARCHITECTURE MIX OF THIS
SETUP LOOK LIKE IN REALITY?

8. • System couplings underperformed or were very opaque
• Missing accountability of specific operations
• High turnaround times and immense debug complexities when issues showed up
• Debugging could only be performed manually
• No simple real-time status was available
• Throughput and peak loads are often a question mark
RESULTS
• Many hours of expensive investigation, without a catalysing fundamental change
• Each time, only the operational status was restored. Underlying causes remained
unchanged
WHAT KIND OF PROBLEMS
SHOWED UP DURING USAGE?

9. • Decentralized and fragmented nature of many solutions
• Processing jumping between systems and locations, depending on the
solution setup
• Inconsistent information storage between solutions
• No complete, centralized accounting of all processes
• No easy way to see the big picture or evaluate it in detail
“You are at ground level, but need eyes in the sky”
WHAT WERE THE SOURCES
OF THESE PROBLEMS?

10. • Message delivery from source systems to subscribers
• Complicated queueing system with IN, OUT and external message-queues
in-between
A CONCRETE EXAMPLE
ELASTICSEARCH RELATIONAL
DATABASES
AMQ IN
AMQ OUT
RECEIVED
ACK
DELIVERED
ACK
D
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R
E
D
A
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K
R
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C
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I
V
E
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A
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IN
RECEIVED
ACK
RECEIPT
ACK
RECEIVED:
1:1
EXTERNAL
OUT
DELIVERED
ACK
RECEIPT
ACK
DELIVERED:
1:N
EXTERNAL
DB

11. 36
CLUSTERED
SETUP
• 2 data centers in an
ACTIVE/ACTIVE state
• Implemented in JAVA
• About 30 connected Parties
• Growing rapidly
SOME SOLUTION METRICS OF THE EXAMPLE
MACHINES
5
SPLIT UP
PROCESSING
• Jobs jump between
components in an ASYNC
manner
• Store-and-forward with
duplication in-process
• Transaction volumes double
EVERY YEAR
LOGICAL COMPONENTS
3
DEPLOYED
IN CHAIN
• Every change has to go from
development to acceptance to
production
• Mission critical backbone of
governmental infrastructure
• High-reliability and legal
accountability is a MUST
DEPLOYMENT STAGES

12. • Through asynchronicity and decentralization within the solution, measuring
became a jigsaw puzzle
• Performance optimizations without measurements are very problematic
• It was not possible to quickly trace anything in the system…
Manual track-and-trace needed 24 days PER MESSAGE!
• If manual intervention had to occur, it was a laborious process with much
fiddling in different places
PROBLEMS THAT SHOWED UP

13. Catalyst for change was the long reaction times and many unanswered
questions.
What is going on? Where? How can we see this ASAP?
After lengthy brainstorming, our conclusions looked like this:
• We need some form of APM
• With many APM solutions in the market, only Elastic covered all the use-cases
• Fits the licensing in this area, by being Enterprise Open-Source
(a hard governmental requirement)
• Technical advantages: distributed nature, speedy and fail-safe, scales rapidly,
Kibana brings immediate added benefit
WHAT NOW? HOW CAN WE
GET THIS UNDER CONTROL?

14. • Through the partnership, we had a reliable source of knowledge and
experience with the solution stack by our side
• Training and direct contact brought our people up to speed in no time
• This cut down the time we needed to implement the solution and
ramp it up in production
• Easy upscaling became possible
PARTNERING WITH ELASTIC
WAS THE KEY ENABLER
+

15. • Previously unknown areas of problems could be explored at ease
• Not only APM was provided, but any kind of distilled information needed
WHAT DID THAT MEAN FOR
THE DUTCH GOVERNMENT?

16. TIMING ABILITY KPI
• Throughput is one of several
key KPIs. It is benchmarked by
messages per second
• 100% at: 100 msg/s
• Before APM 10 msg/s
• After APM 150 msg/s
HOW HAS THE CUSTOMERS’
EXPERIENCE CHANGED NOW
DAYTODAY?
• Targeted optimizations with
measurable results are
possible now
• A general feeling of control
and insight is prevalent now
• Reaction time for message
debugging decreased:
24 days TO MERE MINUTES
• Operational status has
improved significantly.
Breakdowns and issues
reduced to 1/10th

17. Oh heavens no. This is only the beginning.
• Currently, Capgemini is ramping up the Elastic offerings in other sectors of the market
– with equally transformative results
• ML capabilities are becoming more interesting and in-demand with our customers
• Search as a use-case is becoming more interesting
• SIEM/SOC is gaining momentum as well
This technology is the future of how we understand our solutions.
Capgemini has identified Elastic service offerings as a growth sector in 2021
SOUNDS LIKE ONE PROBLEM
LESS ON EVERYONE’S PLATE.
IS THAT IT?

18. THANK YOU!