Month: May 2016

Intro to PaaS

Today we are going to move up the stack. We will first focus on the Oracle solutions talking about the different platform as a service offerings. It is important to spend a little time reviewing this layer because what one company calls PaaS, another calls SaaS. The best way to get started is to go to cloud.oracle.com and look at the pull downs at the top of the screen. We see Infrastructure, Platform, and Applications.

When we pull down the Platform menu we see that there are different areas that we can dive into.

Data management is the first area that we will review. This is basically a way to aggregate and look at data. We can store data in a database, store on-premise databases into the cloud, store data in NoSQL repositories, and do analytics on a variety of data with Big Data Preparation and Big Data services. All of these involve pulling data into a repository of some type and performing queries against the repository. The key difference is the way that the data is stored, how we can ask questions, and the results that we get back. At this point we will not dive into any of these deeply but at a later point dive deep into the database and database backup.

The Application Development is moving farther away from the technology of storing data and moving closer to how we present data to users. The Java platform, for example, allows us to do things like create a shopping cart or hosting more complex applications in a Java repository or container. The Mobile Cloud Service allows us to dive into existing applications and present a user interface to iPhones, Android Phones, and tablets. The idea is to customize existing web and fat clients into a mobile format that can be consumed on mobile devices. The Messaging Cloud Service is a messaging protocol that allows for transactions in the cloud. If you are looking at connecting different cloud services together it allows you to serialize the communication between vendors for a true transactional experience. The Application Container Cloud is a lightweight Java container allowing you to upload and run java applications but without access to the operating system. This is a shared multi-tenant version of a WebLogic server. The Developer Cloud Service is a DevOps integration for the Java and Database services. This service is an aggregation of public domain components used to develop microservices at the database or java layer. The Application Builder Cloud Service is a cloud based REST api development interface allowing you to integrate with Application software in the Oracle Cloud as well as other Clouds. The API Catalog is a way of publishing the REST apis that you have and expose them to your customers.

The Content and Process Cloud Services are an aggregation of services that address group communications as well as business process flow. The Documents Cloud Service is a way of file sharing on the web. The Process Cloud Service is an extension that allows you to launch business processes (think Business Process Manager or BPM) in the cloud. The Sites Cloud Service is a web portal interface that takes documents and processes and aggregates them into a single cloud site allowing you to take a wiki like presentation but put business processes into the presentation. The Social Network Cloud Service allows you to integrate social network services like Facebook and Twitter into your web presence. It allows you to integrate these services as well as search these repositories for information relating to your company.

The Business Analytics part of Platform services provides data visualization and analytic tools as well as data aggregation utilities. The Business Intelligence component is the traditional BI package that allows users to create custom queries into your database. The Big Data Preparation allows you to aggregate data from a variety of sources into a Big Data repository. The Big Data Discovery allows you to look at your data in a variety of ways and generate reports based on your data and views of data. The Data Visualization Cloud Service allows you to view and analyze your data from different perspectives. This is similar to the BI and Big Data but looks at data slightly differently. The Internet of Things Cloud Service allows you to aggregate monitoring and measuring devices into a repository.

The Cloud Integration part of Platform services is the traditional data aggregation tools from other repositories. The Integration Cloud Service allows you to aggregate traditional SaaS vendors to unify fields like how a customer is defined or what data elements are incorporated into a purchase order. The SOA Cloud Service is implementation of the Oracle SOA Suite in the cloud. The GoldenGate Cloud Service is an implementation of the Oracle Golden Gate software that allows you to take data from different databases and synchronize the different repositories independent of the database vendor. The Internet of Things Cloud Service is the same listed in the Business Analytics section mentioned before.

The Cloud Management part of Platform services allows you to take the log files that you have inside your data center and analyze them for a variety of things. You can aggregate your log files into the Log Analytics Cloud Services to look for patterns, intrusion attempts, and problems or issues with services. The IT Analytics Cloud Service looks at log files and looks for trends like disks filling up, processors being used or not used appropriately. The Application Performance Cloud Service looks at log files to look at how systems and applications are operating rather than how systems are working rather than how components are working.

In Summary, we looked at an overview of the Platform as a Services offered by Oracle. Unfortunately, the variety of topics are too great for one blog. We did a high level overview of these services. In upcoming blogs we will dive deeper into each of these services and look at not only what they are but how they work and how to provision these services. We will also compare and contrast how these services compare to services offered by Amazon and Azure as we dive into each service.

storage cloud appliance in the cloud

Last week we focused on getting infrastructure as a service up and running. I wanted to move up the stack and talk about platform as a service but unfortunately, I got distracted with yet another infrastructure problem. We were able to install the storage cloud appliance software in a virtual machine but how do you install this in a compute cloud instance? This brings up two issues. First, how do you run a Linux 7 – 3.10 kernel in the Oracle Compute Cloud Service. Second, how do you connect and manage this service both from an admin perspective and client from another compute engine in the cloud service.

Let’s tackle the first problem. How do you spin up a Linux 7 – 3.10 kernel in the Oracle Compute Cloud Service? If we look at the compute instance creation we can see what images that we can boot from.

There is not Linux 7 – 3.10 kernel so we need to download and import and image that we can boot from. Fortunately, Oracle has gone through a good importing a bootable image tutorial. If we follow these steps, we need to first download a CentOS 7 bootable image from cloud.centos.org. The cloud instance that we use is the CentOS-7-x86_64-OracleCloud.raw.tar.gz. We first download this to a local directory then upload it to the compute cloud image area. This is done by going to the compute console and clicking on the “Images” tab at the top of the screen.

We then upload the tar.gz file that is a bootable image. This allows us to create a new storage instance that we can boot from. The upload takes a few minutes and once it is complete we need to associate it with a bootable instance. This is done by clicking on the “Associate Image” button where we basically enter a name to use for the operating system as well as description.


Note that the OS size is 9 GB which is really small. We don’t have a compute instance at this point. We either need to create a bootable storage element or compute instance based on this image. We will go through the storage create first since this is the easiest way of getting started. We first have to change from the Image tab to the Storage tab. We click on the Create Storage Volume and go through selection of the image, storage name, and size. We went with the storage size rather than resizing the storage we are creating.



At this point we should be able to create a compute instance based on this boot disk. We can clone the disk, boot from it, or mount it on another instance. We will go through and boot from this instance once it is created. We do this by going to the Instance tab and clicking on Create Instance. It does take 5-10 minutes to create the storage instance and need to wait till it is completed before creating a compute instance. An example of a creation looks like



We select the default network, the CentOS7 storage that we previously created, the 2016 ssh keys that we uploaded, and review and launch the instance.




After about 15 minutes, we have a compute instance based on our CentOS 7 image. Up to this point, all we have done is create a bootable Linux 7 – 3.10 kernel. Once we have the kernel available we can focus on connecting and installing the cloud storage appliance software. This follows the making backup better blog post. There are a couple of things that are different. First, we connect as the user centos rather than oracle or opc. This is a function of the image that we downloaded and not a function of the compute cloud. Second, we need to create a second user that allows us to login. When we use the centos user and install the oscsa_install.sh script, we can’t login with our ssh keys for some reason. If we create a new user then whatever stops us from logging in as the centos user does not stop us from logging in as oracle, for example. The third thing that we need to focus on is creating a tunnel from our local desktop to the cloud instance. This is done with ssh or putty. What we are looking for is routing the management port for the storage appliance. It is easier to create a tunnel rather than change the management port and opening up the port through the cloud firewall.





From this we execute the commands we described in the maker backup better blog. We won’t go through the screen shots on this since we have done this already. One thing is missing from the screenshot, you need to disable selinux vy editing /etc/sysconfig/selinux. You need to disable SELINUX by editing the file and rebooting. Make sure that you add a second user before rebooting otherwise you will get locked out and the ssh keys won’t work once this change is made.

The additional steps that we need to do are create a user, copy the authorized_keys from an existing user into the .ssh directory, change the ownership, and assign a password to the new user, and add the user to /etc/sudoers.

useradd oracle
mkdir ~oracle/.ssh
cp ~centos/.ssh/authorized_keys ~oracle/.ssh
chown -R oracle ~oracle
passwd oracle
vi /etc/sudoers

The second major step is to create an ssh tunnel to allow you to connect in from your localhost into the cloud compute service. When you create the oscsa instance it starts up a management console using port 32769. To tunnel this port we use putty to connect.





At this point we should be able to spin up other compute instances and mount this file system internally using the command

mount -t nfs -o vers=4,port=32770 e53479.compute-metcsgse00028.oraclecloud.internal:/ /local_mount_point

We might want to use the internal ip address rather than the external dns name. In our example this would be the Private IP address of 10.196.89.62. We should be able to mount this file system and clone other instances to leverage the object storage in the cloud.

In summary, we did two things in this blog. First, we uploaded a new operating system that was not part of the list of operating systems presented by default. We selected a CentOS instance that conforms to the requirements of the cloud storage appliance. Second, we configured the cloud storage appliance software on a newly created Linux 7 – 3.10 kernel and created a putty tunnel so that we can manage the directories that we create to share. This gives us the ability to share the object storage as an nfs mount internal to all of our compute servers. It allows for things like spinning up web servers or other static servers all sharing the same home directory or static pages. We can use these same processes and procedures to pull data from the Marketplace and configure more complex installations like JD Edwards, PeopleSoft, or E-Business Suite. We can import a pre-defined image, spin up a compute instance based on that image, and provision higher level functionality onto infrastructure as a service. Up next, platform as a service explained.