NoSQL and Cloud Services - Philip Balinow, Comfo

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This document provides definitions and discusses advantages of cloud computing and big data. It defines cloud computing as distributed computing over a network that allows programs to run across multiple connected computers. Big data is defined as extremely large and complex datasets that are difficult to process using traditional methods. The document outlines the pros of cloud computing, including better hardware utilization, scalability, usage-based pricing, and no upfront costs. It also discusses challenges like continuously changing workloads and the need for automation, horizontal scaling, and asynchronous task execution in the cloud.

Introduction into
Cloud Computing
philip.balinov@komfo.com
DevOps Engineer

SOME DEFINITIONS
def. CLOUD COMPUTING
def. BIG DATA

SOME DEFINITIONS
def. CLOUD COMPUTING
- distributed computing over a network
- the ability to run a program or application on
many connected computers at the same time.
def. BIG DATA
- data sets so large and complex that it becomes
difficult to process using traditional data
processing applications

SOME DEFINITIONS, CONTD.
Q: No, seriously. What is the Cloud?
A: Well, there are three types
 Infrastructure-as-a-Service
 Platform-as-a-Service
 Software-as-a-Service

THE CLOUD – PROS AND CONS
WHY CLOUD COMPUTING IS SO GREAT
 Better hardware utilization
 Economy of scale
 Usage-based pricing
 In-built resilience (here be monsters)
 No front-up costs
 No long-term contracts

Retail
Finance
E-Commerce
Telecommunicatio
n
B2B
Publishing/Media
Government & NGO
Automotive
Travel
KOMFO'S CLIENTS

OUR TECHNOLOGY

PHP, Python, C

MySQL

MongoDB, Elasticsearch

Javascript (node.js)

Ruby

Freedom to use any tool fit for the job

KOMFO MAIN CHALLENGES
Continuously changing workload
Fast feature changes
BigData
(Predictive) Analytics
Security
Availability

NoSQL and Cloud Services - Philip Balinow, Comfo

HOW TO USE THE CLOUD

Automation

Horizontal scaling

Break tasks into many small sub-tasks

Synchronize all the workers

Write for eventual consistency

HOW TO USE THE CLOUD

Beware! There are traps*
*Minimally shared with fair weighting. Allows burst when
idle resources are available. In rare cases, resources
may be throttled back under heavy host contention.
–
**Disk I/O is shared across the host.
–
***A vCPU corresponds to a physical CPU thread.
–

HOW TO USE THE CLOUD

There are more traps*

Coordinate tasks – good messaging
system (AMQP, DB, MemCached)

Asynchronous task execution (see
above, also API Callback hooks)

Implement transactions in software

CLOUD ARCHITECTURE

Messaging

Ensure communication between dynamic
number of nodes

Message-oriented middleware

Exactly-once delivery

At-least-once delivery

Transaction-based delivery

Timeout-based delivery

MIX & MATCH

Crunch numbers in the cloud

Application servers

Slow running tasks

Temporary services

Test servers

Automation – automatic deployment of multi-
tiered environments

MIX & MATCH, CONTD.

Traditional servers for:

Incompatible apps (single-threaded, memory,
disk intensive, specialized hardware) do not
work well in cloud environments

Database servers are best kept on dedicated
machines

OK, so we have an (endlessly)
scalable cloud app now.
What are we forgetting?

DATABASES, NOSQL

def. NoSQL

a mechanism for storage and retrieval of data
that is modeled in means other than the tabular
relations used in relational databases.

DATABASES

Postgres, Hadoop, MongoDB, Cassandra, Riak

In-memory dataset for faster operation

No predefined structure

Integrated sharding, load-balancing and failover

Versatility - can be used for anything from data
storage to real-time messaging to search indexes

DATABASES

Use the best tool for the job depending on the task

NoSQL Advantages

Some sources generate a lot of data

Complex interconnections, cyclical
dependencies

Aggregations must be performed on both new
and old data

Structure of foreign sources may change on
short notice

DATABASES

Use the best tool for the job depending on the task

NoSQL Disadvantages (Classic SQL advantages)

Not ACID compliant

No transactions

No relations between data

Lack of structure means aggregations are slow

DATABASES, LONG TERM STRATEGY

Data quickly becomes irrelevant

Archive it, but keep it accessible

Online Data Warehouse solutions

Amazon Redshift

Keep Everything

Terabytes for pennies

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The buzz around the Linux kernel technology eBPF is growing quickly and it can be hard to know where to start or how to keep up with this technology that is reshaping our infrastructure stack. In this talk, Bill will trace how he got into eBPF, explore some of the applications leveraging eBPF today, and teach others how to dive into the hive of activity around eBPF. People just beginning with eBPF will learn how eBPF makes it possible to have efficient networking, observability without instrumentation, effortless tracing, and real-time security (among other things) without needing your own kernel team. Those already familiar with eBPF will get an overview of the eBPF landscape and learn about many new and expanding eBPF applications that allow them to harness the power without needing to dive into the bytecode. The audience will walk away with an understanding of the buzz around eBPF and knowledge of new tools that may solve some of their problems in networking, observability, and security.

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stackconf 2024 | On-Prem is the new Black by AJ Jester

NETWAYS

In a world where Cloud gives us the ease and flexibility to deploy and scale your apps we often overlook security and control. The fact that resources in the cloud are still shared, the hardware is shared, the network is shared, there is not much insight into the infrastructure unless the logs are exposed by the cloud provider. Even an air gap environment in the cloud is truly not air gapped, it’s a pseudo-private network. Moreover, the general trend in the industry is shifting towards cloud repatriation, it’s a fancy term for bringing your apps and services from cloud back to on-prem, like old school how things were run before the cloud was even a thing. This shift has caused what I call a knowledge gap where engineers are only familiar with interacting with infrastructure via APIs but not the hardware or networks their application runs on. In this talk I aim to demystify on-prem environments and more importantly show engineers how easy and smooth it is to repatriate data from cloud to an on-prem air gap environment.

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stackconf 2024 | Using European Open Source to build a Sovereign Multi-Cloud ...

NETWAYS

The European Commission has clearly identified open source as a strategic tool for bringing some balance to an EU cloud market currently dominated by a handful of non-EU hyperscalers. Part of that commitment comes through a series of ambitious, multi-million EU projects like the SIMPL platform for Data Spaces and the multi-country “Important Project of Common European Interest on Next Generation Cloud Infrastructure and Services” (IPCEI-CIS). For the first time in the history of the European Union, it is the EU industry who will be leading large-scale open source projects aimed at building European strategic technologies. In this talk we will explain in detail how specific European open source technologies are being brought together as part of some of those projects to start building Sovereign Multi-Cloud solutions that ensure interoperability and digital sovereignty for European users while preventing vendor lock-in in the cloud market, opening up competition in the emerging 5G/edge.

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NoSQL and Cloud Services - Philip Balinow, Comfo

1. Introduction into Cloud Computing philip.balinov@komfo.com DevOps Engineer

2. SOME DEFINITIONS def. CLOUD COMPUTING def. BIG DATA

3. SOME DEFINITIONS def. CLOUD COMPUTING - distributed computing over a network - the ability to run a program or application on many connected computers at the same time. def. BIG DATA - data sets so large and complex that it becomes difficult to process using traditional data processing applications

4. SOME DEFINITIONS, CONTD. Q: No, seriously. What is the Cloud? A: Well, there are three types  Infrastructure-as-a-Service  Platform-as-a-Service  Software-as-a-Service

5. THE CLOUD – PROS AND CONS WHY CLOUD COMPUTING IS SO GREAT  Better hardware utilization  Economy of scale  Usage-based pricing  In-built resilience (here be monsters)  No front-up costs  No long-term contracts

6. Retail Finance E-Commerce Telecommunicatio n B2B Publishing/Media Government & NGO Automotive Travel KOMFO'S CLIENTS

7. KOMFO PLATFORM WORKFLOW OVERVIEW

8. EXTERNAL PROVIDERS

9. OUR TECHNOLOGY  PHP, Python, C  MySQL  MongoDB, Elasticsearch  Javascript (node.js)  Ruby  Freedom to use any tool fit for the job

10. KOMFO MAIN CHALLENGES Continuously changing workload Fast feature changes BigData (Predictive) Analytics Security Availability

12. HOW TO USE THE CLOUD  Automation  Horizontal scaling  Break tasks into many small sub-tasks  Synchronize all the workers  Write for eventual consistency

13. HOW TO USE THE CLOUD  Beware! There are traps* *Minimally shared with fair weighting. Allows burst when idle resources are available. In rare cases, resources may be throttled back under heavy host contention. – **Disk I/O is shared across the host. – ***A vCPU corresponds to a physical CPU thread. –

14. HOW TO USE THE CLOUD  There are more traps*  Coordinate tasks – good messaging system (AMQP, DB, MemCached)  Asynchronous task execution (see above, also API Callback hooks)  Implement transactions in software

15. CLOUD ARCHITECTURE  Messaging  Ensure communication between dynamic number of nodes  Message-oriented middleware  Exactly-once delivery  At-least-once delivery  Transaction-based delivery  Timeout-based delivery

17. MIX & MATCH  Crunch numbers in the cloud  Application servers  Slow running tasks  Temporary services  Test servers  Automation – automatic deployment of multi- tiered environments

18. MIX & MATCH, CONTD.  Traditional servers for:  Incompatible apps (single-threaded, memory, disk intensive, specialized hardware) do not work well in cloud environments  Database servers are best kept on dedicated machines

19. OK, so we have an (endlessly) scalable cloud app now. What are we forgetting?

20. DATABASES, NOSQL  def. NoSQL  a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases.

21. DATABASES  Postgres, Hadoop, MongoDB, Cassandra, Riak  In-memory dataset for faster operation  No predefined structure  Integrated sharding, load-balancing and failover  Versatility - can be used for anything from data storage to real-time messaging to search indexes

22. DATABASES  Use the best tool for the job depending on the task  NoSQL Advantages  Some sources generate a lot of data  Complex interconnections, cyclical dependencies  Aggregations must be performed on both new and old data  Structure of foreign sources may change on short notice

23. DATABASES  Use the best tool for the job depending on the task  NoSQL Disadvantages (Classic SQL advantages)  Not ACID compliant  No transactions  No relations between data  Lack of structure means aggregations are slow

24. DATABASES, LONG TERM STRATEGY  Data quickly becomes irrelevant  Archive it, but keep it accessible  Online Data Warehouse solutions  Amazon Redshift  Keep Everything  Terabytes for pennies

25. Summary The cloud rocks, mmkay?

26. Questions?

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