diff --git a/scripts/postprocessing/bottleneck.py b/scripts/postprocessing/bottleneck.py
new file mode 100644
index 0000000..8b94f2f
--- /dev/null
+++ b/scripts/postprocessing/bottleneck.py
@@ -0,0 +1,111 @@
+""" Analize test results for finding bottlenecks """
+
+import sys
+import argparse
+
+import texttable as TT
+
+from collections import namedtuple
+
+
+Record = namedtuple("Record", ['name', 'max_value'])
+
+critical_values = [
+    Record("io_queue", 1),
+    Record("procs_blocked", 1),
+    Record("mem_usage_percent", 0.8)
+    ]
+
+def load_results(begin_time, end_time, rfile):
+    """ Read raw results from dir and return
+        data from provided period"""
+    results = {}
+
+    with open(rfile, "r") as f:
+        for line in f:
+
+            if len(line) <= 1:
+                continue
+            ttime, _, raw_data = line.partition(" : ")
+            raw_data = raw_data.strip('"\n\r')
+            itime = float(ttime)
+            if itime >= begin_time and itime <= end_time:
+                addr, data = eval(raw_data)
+                sid = data.pop("source_id")
+                data.pop("time")
+                serv = "{0}({1})".format(addr[0], sid)
+                serv_data = results.setdefault(serv, {})
+                for key, value in data.items():
+                    # select device and metric names
+                    dev, _, metric = key.partition(".")
+                    # create dict for metric
+                    metric_dict = serv_data.setdefault(metric, {})
+                    # set value for metric on dev
+                    cur_val = metric_dict.setdefault(dev, [])
+                    cur_val.append(value)
+        print results
+        return results
+
+
+
+def print_bottlenecks(data, params):
+    """ Print bottlenecks in table format,
+        search in data by fields in params"""
+    tab = TT.Texttable()
+    tab.set_deco(tab.VLINES)
+
+    header = ["Server, device", "Critical value"]
+    tab.add_row(header)
+    tab.header = header
+
+    rows = []
+    val_format = "{0}: {1}, {2} times it was >= {3}"
+    for node, metrics in data.items():
+        node_rows = []
+        for metric, max_value in params:
+            if metric in metrics:
+                item = metrics[metric]
+                # find max val for dev
+                # count times it was > max_value
+                for dev, vals in item.items():
+                    num_l = 0
+                    max_v = -1
+                    for val in vals:
+                        if val >= max_value:
+                            num_l += 1
+                            if max_v < val:
+                                max_v = val
+                    if num_l > 0:
+                        c_val = val_format.format(metric, max_v,
+                                                  num_l, max_value)
+                        node_rows.append([dev, c_val])
+        if len(node_rows) > 0:
+            rows.append([node, ""])
+            rows.extend(node_rows)
+
+    for row in rows:
+        tab.add_row(row)
+
+    print tab.draw()
+
+
+
+def parse_args(args):
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-t', '--time_period', nargs=2,
+                        type=float,
+                        help="Begin and end time for tests")
+    parser.add_argument('sensors_result', type=str,
+                        default=None, nargs='?')
+    return parser.parse_args(args[1:])
+
+
+def main(argv):
+    opts = parse_args(argv)
+
+    results = load_results(opts.time_period[0], opts.time_period[1], opts.sensors_result)
+
+    print_bottlenecks(results, critical_values)
+
+if __name__ == "__main__":
+    exit(main(sys.argv))