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Emerging trends
in software development:
The next generation of storage
Donnie Berkholz, Ph.D.
Research Director — Development, DevOps & IT Ops
SNIA Storage Developer Conference, Sept 2015
Technology
adoption
is increasingly
bottom-up
2
Wikipedia: G.dallorto
App-dev workloads are quickly moving to the cloud
3
Current Future
59.0%
7.9%
14.2%
5.2%
6.6%
7.1%
On-Premises, Non-Cloud
Off-Premises, Non-Cloud
On-premises Private Cloud
Hosted Private Cloud
Infrastructure-as-a-Service
(IaaS)/Public Cloud
Software-as-a-Service (SaaS)
n = 146
37.3%
6.1%
19.1%
9.9%
15.2%
12.4%
n = 134
Source: 451 VotE Cloud, Q2 2015
CLOUD COMPUTING
Q1 2015
Q. Estimate the percentage of your organization’s data currently stored in off premises cloud environments? Q. How many terabytes of data does your
company currently have under management across all environments?
*Terabytes of Data Stored in Off-Premises Cloud" is calculated from an organization's total data and the percent they store in off-premises cloud
environments.
Data Storage - Cloud Respondents
4
20.0%
7.5%
7.3%
6.3%
42.8%
16.2%
> 1000TB
750TB-1000TB
500TB-749TB
250TB-499TB
10TB-249TB
<10TB
Percent of Sample
n =877
Percent of Organization’s Data
Stored in Off-Premises Cloud
Total Data at Organization
Source: 451 Research, Voice of the Enterprise: Cloud Computing Q1 2015
3.8%
1.4%
2.5%
3.1%
42.0%
47.1%
> 1000TB
750TB-1000TB
500TB-749TB
250TB-499TB
10TB-249TB
<10TB
Percent of Sample
n =766
Terabytes of Data Stored in Off-Premises
Cloud *
7.8%
6.4%
6.9%
14.6%
64.3%
> 80%
60%-80%
40%-59%
20%-39%
< 20%
Percent of Sample
n =896
The new stack?
5
An infinite array of possible stacks.
The API
economy
6
What do enterprises think of storage vendors?
7
Source: 451 Storage Wave 19, June 2015; n=250ç
Development trends
that will transform
storage use
8
9
Docker Docker Docker
Source: 451 Research, “Now Shipping: The Docker and containers ecosystem rapidly takes shape”
Developers
love
Docker
Donnie Berkholz Source: http://www.slideshare.net/dberkholz/is-your-community-healthy-metrics-on-the-top-cm-software
10
*
But it’s not just a toy
11
21%}
Source: 451 VotE Cloud, Q1 2015; n=991
3.1%
19.8%
56.1%
10.7%
3.9%
4.2%
2.1%
Unfamiliar
No Plans
Discovery and Evaluation
Running Trials/Pilot Projects
Used for Test and Development
Environment
Initial Implementation of Production
Applications
Broad Implementation of
Production Applications
Docker to microservices
12
Loosely coupled teams
“ One of the biggest changes is that we no longer have
an official ‘architecture’ team. Instead, we have made
‘architecture’ an ‘ingredient’ on each of our teams.”
13
http://tech.gilt.com/post/102628539834/making-architecture-work-in-microservice
– Lauri Apple, Gilt Groupe, 14 Nov 2014
The foundation of microservices
14
15
Disruption in data processing
16
Spark came out of nowhere
Donnie Berkholz Source: http://redmonk.com/dberkholz/2015/03/13/the-emergence-of-spark/
17
On Hacker News, too
Donnie Berkholz Source: http://redmonk.com/dberkholz/2015/03/13/the-emergence-of-spark/
The market is coming
18
Source: 451 Research Total Data: Platforms & Analytics Market Monitor, May 2015
19
Storage-class memory
Concurrency for developers
20
Donnie Berkholz Source: http://redmonk.com/dberkholz/2014/03/18/go-the-emerging-language-of-cloud-infrastructure/
Development trends
that will transform
storage vendors
21
22
What in the world
is DevOps, anyhow?
23
Agile, truly tip to tail
Business to customer
3 pillars of DevOps
24
Culture
Automation
Measurement
25
Culture:
Tear down all the silos
Flickr: kalandrakas
26
Flickr: respresFlickr: hartvig, snapeverything, roymaloon
Automation:
Pets vs Cattle
Automation: Infrastructure as code
27
Knight Capital and the $460 million bug
28
Wikipedia: Jericho
Release management – quarterly to daily
Gary Gruber, HP
Automation: Continuous delivery
29
continuousautomation.com
Measurement: #monitoringsucks/monitoringlove
30
DevOps is reaching DBAs
451 DevOps study, Q3 2014
31
32
33
Adopting open-source technologies
Blogspot: ThatsABigIf
The changing role of standards
34
The changing role of benchmarks
35
Wrapping up
• Docker and microservices will exacerbate hypervisor-style use &
increase demands on the network
• Spark will drive requirements for memory and memory-like storage
• DevOps & continuous delivery will transform how you deliver
storage software
• The interplay between open source, standards and benchmarks
continues to tilt toward agility
36
Global Digital Infrastructure Alliance — 20,000 strong
Share your thoughts, get our data
451alliance.com 37
Storage needs to cope with agility.
Donnie Berkholz
@dberkholz
donnie.berkholz@451research.com
Some images from this presentation
are Creative-Commons licensed.
https://creativecommons.org/licenses/by-sa/
https://creativecommons.org/licenses/by/
39

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Emerging trends in software development: The next generation of storage

Editor's Notes

  1. Cathedral, indulgences to bazaar Open source, cloud, DigitalOcean
  2. Future is two years out App dev is 7.8% of workloads, ranked #5 (highest is email/collab at 15.9%) … What does this mean for the data behind the apps?
  3. Data gravity. Still mostly on-prem. … that’s what we’re building, now how are we building it?
  4. Languages, databases, frameworks … What’s driving the way we build technology?
  5. The new mode for access & transfer of data has become APIs Most storage file/block. This is more likely object-driven … why should you and your companies care?
  6. N not large enough for everything Exciting vendors: Pure and EMC
  7. Hypervisors already had randomized I/O, now exacerbated. Flash optimal, tough for SMR Flocker BoF
  8. Explain GitHub, Stars/PRs/Forks
  9. Active-active, cross-DC/cross-region (DynamoDB outage) Distributed datastores Most storage backup/replication is array-/hypervisor-level, not app-level Loosely coupled Business-defined separations. Bounded context based on cross-organizational empathy. Steve Yegge memo — Amazon must be SOA, or you’re fired.
  10. DevOps + microservices Bounded contexts, empathy defined DevOps is how you build and run microservices.
  11. Also note PaaS providers moving to containers
  12. Spark. What is Spark? In-memory compute, can cache to disk. IoT In-memory compute Real-time analytics (streaming), graph, ML (repeated computations in memory) NoSQL at scale – distributed databases (Cassandra)
  13. Spark. What is Spark? In-memory compute, can cache to disk. IoT In-memory compute Real-time analytics (streaming) NoSQL at scale – distributed databases (Cassandra)
  14. Spark, IoT In-memory compute Real-time analytics (streaming) NoSQL at scale – distributed databases (Cassandra)
  15. Hadoop market 26 vendors included 42% CAGR above $100m rev 50% below $100m rev … A couple of quick hits before we get into how you change
  16. Do app devs need to care? Storage round trips much cheaper, how does this change things? Suitable data structures – parallels to Redis/Memcached? IoT (equivalent of moving compute to data as SCM reaches CPU)
  17. Their view: onload/offload and RDMA Mine: functional programming, JVMs, Go, distributed systems, Spark, etc.
  18. OODA loops
  19. How can SP do this? Marketing, PS, dev-focused services, SDKs etc
  20. Where storage and networking fit in. APIs, vanilla (SDS, Cumulus, etc)
  21. Release management – quarters to weeks to days to hours Gary Gruver, HP
  22. Community, UX Keep using cattle metaphor Storage – metrics output, APIs
  23. Seen a lot of open source on the agenda here What are your criteria?
  24. “s3 api” vs “Storage api” Agile. Ad hoc. Agile foundations
  25. Jepsen Session from Mai Zheng from NMSU Open-source benchmarks