Adopting Hadoop to manage your Big Data is an important step, but not the end-solution to your Big Data challenges. Here are some of the additional considerations you must face:
Choosing the right cloud for the job: The massive computing and storage resources that are needed to support Big Data applications make cloud environments an ideal fit, and more than ever, there is a growing number of choices of cloud infrastructure types and providers. Given the diverse options, and the dynamic environments involved, it becomes ever more important to maintain the flexibility for all your IT needs.
Big Data is a complex beast: It involves many and different moving parts, in large clusters, and is continually growing and evolving. Managing such an environment manually is not a viable option. The question is, how can you achieve automation of all this complexity?
The world beyond Hadoop: Big Data is not just Hadoop – there is a whole rapidly growing ecosystem to contend with, including NoSQL, data processing, analytics tools… As well as your own application services. How can you manage deployment, configuration, scaling and failover of all the different pieces, in a consistent way?
In this session, you’ll learn how to deploy and manage your Hadoop cluster on any Cloud, as well as manage the rest of your big data application stack using a new open source framework called Cloudify.
3. Big Data In The Cloud
2.7 ZB
Global Digital Data
0.5
Petabytes
43% think that data
analytics could be improved in their
Two years tweets
organization if data analytics was part of
cloud services
66% Will or plan to use Big
Data in the cloud
3
4. Large ISV Case Study
• Application
– Call Center surveillance
• Background
– Previously – voice data
• Goal for a new system
– Monitor data & voice
– Multiple data sources
– Advanced correlations
10. Big Data in the Cloud- 3 Reasons
• Skills
– Do you really need/want this all in-
house?
• Huge amounts of external data.
Holger Kisker – Does it make sense to move and
manage all this data behind your
firewall?
• Focus on the value of your data
– Instead of big data management.
11. • Auto start VMs
• Install and configure
app components
• Monitor
• Repair
• (Auto) Scale
• Burst…
25. Consistent Management
Recipes consistent description for running any app:
What middleware services to run
Dependencies between services
How to install services
Where application and service binaries are
When to spawn or terminate instances
How to monitor each of the services.
® Copyright 2012 GigaSpaces Ltd. All Rights
25
Reserved
28. Automation across the stack
1 Upload your recipe.
2 Cloudify creates VM’s & installs agents
3 Agents install and manage your app
4 Cloudify automate the scaling
31. Try a simple demo yourself
launch.cloudifysource.org/d
32. Large ISV Case Study
• Application
– Call Center surveillance system
• Background
– Previously – voice data
• Goal for a new system
Monitor data & voice
Multiple data sources
Advanced correlations Mission
Accomplished
33. Additional Benefits
• True Cloud Economics
• One product -> any
Customer Environment
• Increased Agility
GigaSpaces Big Data Survey:http://www.gigaspaces.com/sites/default/files/product/BigDataSurvey_Report.pdfForbes on Big Data & Cloud http://www.forbes.com/sites/forrester/2012/08/15/big-data-meets-cloud/38% of all companies from our survey are planning a BI SaaS project before the end of 2013. Many of those respondents (27%) plan to complement their existing BI solutions and a smaller number (11%) actually plan to fully replace their existing BI with a cloud solutionForrester:This year we will hit a volume of 2.7 zettabytes of global digital data ~20% of all tweets include a link that needs to be opened to understand its context.[ii] All tweets from the past two years take 0.5 petabytes to store; it simply doesn’t make sense for every company interested in social media to start storing the same big data in-house.http://www.globaltelecomsbusiness.com/article/3133566/Big-data-becomes-priority-as-executives-tackle-complexity-of-business-analytics.htmlCompanies are most interested in getting access to data in real time (54%), accessing data from multiple devices (51%) and accessing data from remote/flexible locations (44%). Yet, getting access to data in real time emerges as the biggest challenge for companies (52%) along with speed of data delivery (50%); • 43% think that data analytics could be improved in their organisation if data analytics was part of cloud services delivered with third-party expertise.
Big data requires a spectrum of advanced technologies, skills, and investments. Do you really need/want this all in-house?Big data includes huge amounts of external data. Does it make sense to move and manage all this data behind your firewall?Big data needs a lot of data services. Focus on the value of your differentiated data analysis instead of big data management.http://www.forbes.com/sites/forrester/2012/08/15/big-data-meets-cloud/
Consistent Management: Making the deployment, installation, scaling, fail-over looks the same through the entire stack